Factors Blog

Search marketing with Google Ads is kinda cool. It helps users who are looking for specific information, products, or services connect with businesses looking to sell specific information, products or services — all through a wonderfully powerful, complex search engine. But how does search marketing work? More specifically, how does keyword matching work in the latest iteration of Google Ads? Let’s find out…

How does keyword matching work on Google Ads?

There are 7 steps involved in Google Search Ads to connect the right audience with the right message using keyword matching. Here’s how it works:

1. First, a user types a search query into Google. Google then processes this text against spell-checks, synonyms, and related terms to form what’s called the “retrieval query”. This retrieval query wrangles all relevant search ad keywords that could be served into a set. 

2. From this set of keywords from the retrieval query, Google verifies eligibility based on keyword match type, campaign, ad group, etc. This is performed using advanced machine learning and natural language tech to understand and optimize matching for intent and relevance. Other factors considered by Google are budget, geo, negative keywords, creatives, landing page, time of day, etc. 

3. When choosing from multiple eligible keywords from the same account (For example, if company X bids on both “B2B marketing analytics tools” and “B2B marketing analytics software”), Google will prioritize those keywords that are closer to being an exact match to the search term. So if a user searches “marketing analytics software”, they will receive the former search ad. Once filtered down, Google has its set of ad groups with eligible, relevant keywords.

4. With this set of ad groups containing eligible keywords, Google’s responsive search ads creative system will automatically rally the “best performing creative — including headline and description” for the user based relevance.

5. Next, we arrive at the stage wherein bids are calculated using Ad Rank. Ad Rank is a scoring system that assigns value to ads to determine if or not your ad will be presented to the audience. Of course, your bid amount is an important factor in determining Ad Rank as well. 

6. Here, Google Ads chooses the optimal combination of ad relevance and ad rank. Once again, Google’s algorithm is looking for landing page quality and keywords in an ad group. The latter implies it’s highly important  to group keywords by theme, to ensure favorability. 

7. The final step is straightforward. Once Google Ads processes all the aforementioned information, each advertiser enters into auction and those advertisements with the highest Ad Rank (including and especially bid amounts) are displayed for your audience to see. 

Keyword match types on Google Ads

As the name suggests, keyword matching matches words and phrases from the search ads you bid on to terms that people actually use when searching. Hence, it’s crucial to bid on the relevant keywords to ensure your ads align with what your audience is looking for. Google Ads offers three match types. The accuracy with which the keyword needs to match a user’s search query will be determined based on match type you choose:

1. [Exact match]

‍As you may have guessed, [Exact match] types require an exact match between the keyword and the search query. For example, if the keyword is “B2B marketing analytics”, only search queries that mean the same, like: “B2B marketing analytics software” or “B2B marketing analytics tools” will trigger the search ad. 

2. “Phrase match”

Phrase matching is marginally less rigid than [Exact match] types. It essentially considers all searches wherein the primary keyword is part of a larger string of search text (i.e. a phrase). For example: “Best software for B2B marketing analytics”

3. Broad match

Broad match provides the most loose matching out of the three match types. It considers the exact keyword, phrases around the keyword and all related terms around the keyword. For example, Google may trigger an ad for the search term “B2B marketing attribution” because it's somewhat related to “marketing analytics” as well. 

Note: In short, Exact match keywords are a subset of Phrase match keywords. And Phrase match keywords are a subset of Broad match keywords. 

Broad Keyword Matching on Google Ads

Google Ads have increasingly been pushing Broad match types as their AI-algorithms continue to improve their understanding of language, intent, relevance, etc. In recent year, keyword matching on Google Ads has evolved from a pure syntax-matching system (wherein a user’s search query text simply matches an advertisers search ad keyword) to a semantics based system (wherein broadly related themes and topics are recognized as relevant enough inquiries to warrant the display of an indirectly relevant search ad). Here are some signals that broad match takes into consideration (in addition to exact keyword and phrases):

1. Other keywords in the ad group: Arguably the most important signal is relevance of other keywords within a specific ad group. For example, if the search term is “salmon sweaters” and your ad group consists of the keywords “orange sweaters”, “red sweaters” and “blue sweaters”, Google Ads will understand that in this case, salmon refers to the colour and not the fish. 

2. Previous searches: Google Ads also takes into account a user's previous search when deciding what ad to present. For example, let’s say a user previously searches for “manchester city vs liverpool football score”. Google uses this historical data in the future so that simply searching “man city vs liverpool” will retrieve the football score without mention of either word.

3. User location: This one is straightforward. Google analyses user location to personalize search results. Eg: B2B SaaS marketing agencies based in New York vs B2B SaaS marketing agencies near me. This may or may not be as relevant to your marketing efforts depending on the type of product you’re selling. Still quite handy to be aware of.

4. Landing page: Last but most definitely not least is an ads landing page. Does the landing page contain relevant keywords? Does it contain quality content — including images and creatives, to ensure a valuable experience for the visitor? These are questions to keep in mind when constructing and improving upon your landing pages. 

And there you have it! An overview into how keyword matching works on Google Ads. 

Curious to learn how Google Analytics compares to Factors.ai? Read on here

Now more than ever, marketing analytics is essential to B2B organizations. A robust analytics framework is a must to better understand how prospects make decisions in the buying journey and plug gaps in the sales funnel. 

However, B2B marketing teams rarely have the resources to build out this framework to collect, analyze, and present data in-house. This is where analytics software comes into play.

Heap is a product and web analytics tool that helps you visualize the buyer journey. But is tracking web analytics enough to get clarity on how prospects make buying decisions?

In this blog, we discuss everything you need to know about Heap and whether it's the right fit for your business needs.

What is Heap Analytics? 

Heap was founded in 2013 in San Francisco and has since become one of the top product analytics software for brands across various niches. ‍

Heap collects data from every part of your website and collates it into easy-to-grasp data analysis using line graphs and funnels. It focuses on customer engagement and activity, highlighting areas in the customer's journey that are not-so-smooth—actionable insights that every brand must own. 

What does Heap do well?

1. Real-time tracking 

Perhaps Heap's most significant advantage is its real-time data collection and analysis, which allows marketers to view visitor activity reports in real time. 

‍This feature can be particularly useful after a website's UI change or a new marketing campaign. Tracking activity in real time can provide immediate insights on what's going well, whether there are any glitches in the customer journey and quick updates on campaign performance across the website. 

2. Retroactive analysis 

Heap performs retroactive analysis, which means it tracks every click and action your visitor takes on your website without you having to instruct it to do the same. 

‍This feature saves an enormous amount of time and effort and provides a large data library for reference at any point in time. Once you integrate Heap with your website, you can examine all of your site's activity and derive insights accordingly—all of this without having to manually set up Heap to track each type of user activity! 

3. ‍Multiple devices 

It's no surprise that users interact differently with a website on a mobile phone than they do on a desktop or laptop. Optimizing one's website for various device types is a great way to ensure a good visitor experience without losing viewers to glitchy interfaces or incomplete website layouts. 

Heap's software tracks website performance across various device types to help you understand where improvement is needed. Marketers can greatly benefit from this feature because solid insights guarantee an effective action plan, which in turn leads to better customer engagement. 

4. Events + Filters 

Customizable building blocks are the greatest tool for any marketer, as each brand has unique goals it wishes to fulfill via an analytics tool. For example, while one brand might want to use Heap to identify friction in the sales funnel, another might want to understand its website heatmap after a marketing campaign and improve website traffic. 

Heap offers features called "Events" and "Filters," which help you visualize your customer journey exactly as you want it, from Stage X to Stage Y, for example. 

Why Heap May Not Be The Best Choice

While Heap offers many effective analytics features, there are a few disadvantages that every website owner must consider when choosing it or any other analytics tool. 

Costs of Data Storage 

Due to its size, storing all of this data can be a hassle for a tool that tracks every single movement across your website, including footer buttons, web page scrolls, hovers, etc. The more data you have in your store, the more complicated it can get to calculate data privacy and protection costs, storage and archiving, and backing up data after regular intervals. Heap may be a good option if you're prepared to store large amounts of website data. 

Tricky UI 

Not all marketers are tech wizards, and Heap's UI, although highly interactive and comprehensive, is difficult to master. The learning curve for anyone wanting to manage their site's Heap dashboard well is quite steep, which is why many marketers opt for analytics tools that are beginner-friendly, user-friendly, and easy to learn, such as Factors and Oribi. 

Limited to website analytics

Website data is just one aspect of tracking analytics. If you truly want to know how prospects make buying decisions, you must capture intent signals from multiple sources, such as LinkedIn and review sites like G2. Only when you get the complete picture can you optimize your marketing campaigns and sales outreach, thereby growing your revenue. 

Why Factors.ai over Heap?

Helps build overall GTM motion 

While Heap is an excellent tool to uncover the customer journey, Factors gives your entire GTM team the insights it needs to build out its sales and marketing engine. Factors offers actionable insights through accurate attribution, making it the perfect tool for your sales and marketing teams to identify and optimize the channels contributing to revenue. 

Comprehensive tracking and reporting

While your website plays a crucial role in attracting prospects, you need deeper insights into how you can turn website visitors into paying customers. Combined with account intelligence and attribution features, Factors allows you to track and consolidate data across your website, CRMs, and MAPs to get a full overview of how you can optimize your offering on your website – a feature currently unavailable in Heap. 

Factors also has robust reporting capabilities, where you can track your KPIs for specific channels. Heap does not track any data beyond your website, so you’ll only get pieces of the puzzle and not the completed picture.

💡Learn how you can use Factors to measure the impact of your marketing campaigns

Cost Effectiveness

While Heap doesn’t reveal its pricing on its website, we’ve researched and found that its estimated price starts from $3600 per year. Factors offers a more cost-effective solution for companies looking to track their performance not just on their website but also in overall marketing efforts. 

💰Check out our pricing here

Invest in the right analytics tool 

If you’re looking for a tool to track website analytics, Heap is a good place to start. However, if you want to go beyond the ordinary and grow pipeline for your business, your search ends with Factors. Speak to our team today to understand how Factors can help you turn intent signals into sales. 

‍It’s official: Italy bans Google Analytics 

After Austria and France, Italy has emerged as the next European nation to ban Google Analytics as a result of data privacy concerns. The ruling was drawn after extensive investigations by Italian data watchdog Garanate and the Italian Data Protection Authority.

The primary argument for the Google Analytics ban is that Google, by American law, must transfer personal user data including IP address, OS, language, browser data and more — from Europe back to the headquarters in the US. For one, the Italian authorities deemed this data flow to be unconstitutional as the personal information being processed was not anonymized. Why is this an issue? Two reasons:

1. US surveillance structures do not satisfy Article 52 of the EU Charter on Fundamental Rights, as discovered by the EU’s Court of Justice.
2. The EU's Court of Justice concluded that cases involving data breach and/or violation lack sufficient judicial redress, leaving EU citizens with little option if such a situation should arise. This does not align with Article 47 of the EU charter. 

“A website using Google Analytics (GA) without the safeguards set out in the EU GDPR violates data protection law because it transfers users' data to the USA, which is a country without an adequate level of data protection” - Italian SA

What does this mean for Google Analytics users in Italy?

Well, the authorities are notifying Italian websites, both public and private, to the illegality of data transfers from Europe to Italy through Google Analytics. The Italian SA has also directed all website operators to verify that the tracking cookies are compliant with standard GDPR regulations. If this is not the case, the Italian SA has provided upto 90 days to implement adequate measures in place to support a compliant data flow. Ultimately, if these requirements are not met, a suspension of Google Analytics data flows to the US will be ordered.

Post 90-days, the Italian SA will continue to verify the compliance of GA data flows to ensure GDPR standards are met by ways of ad-hoc inspections.

“The Italian SA wishes to draw the attention of all the Italian website operators, both public and private, to the unlawfulness of the data transfers to the USA as resulting from the use of GA - partly on account of the many alerts and queries received so far . The Italian SA calls upon all controllers to verify that the use of cookies and other tracking tools on their websites is compliant with data protection law; this applies in particular to Google Analytics and similar services.”

In short, if you’re using Google Analytics in Italy, chances are you’ll need to find a privacy-compliant alternative in coming months. While this may seem like concerning news, it’s actually a fantastic opportunity to pick up a more robust solution.

Looking for Google Analytics alternatives?

Factors.ai has you covered. Factors is, and always will be a privacy-first marketing + web analytics platform. In addition to being GDPR compliant, Factors is compliant with CCPA and PECR as well. What’s more? Factors is SOC2 certified — ensuring industry-standard protection across data security, availability, processing integrity, confidentiality, and privacy. 

Although Google Analytics’s upcoming version, GA4, is touted to have significant privacy improvements, the latest updates suggest no real impact on GDPR compliance. Which is why now is the best time to switch to a robust, reliable, privacy-first solution. 

Still not convinced? Here are a few more reasons why GA4 isn’t really well suited for business anymore. And schedule a personalized demo here to learn why Factors really is the best alternative!

‍Contemporary B2B marketing is closing the gap

In the marketing realm, it’s a common precedent to pit B2B and B2C marketing against each other. And rightly so, given their inherently dissimilar attributes with who they’re selling to, how long it takes to make a purchase, etc. With that said, research and technology have proven there are a lot alike between the two. They might be subtle but understanding those subtleties are impactful for the long haul.

Technology has shown us the prevalence of digital customers in B2B buyer personas is similar to that of B2C. With B2B marketing showing a progressive interest in becoming more brand-oriented, research has shown us the importance of emotional connection at higher levels of a B2B element value. Like in B2C, building a social media presence or making more personalized content to promote branding has shifted the agenda of B2B marketing. To emphasize further, here are 4 things B2B marketing could adopt from B2C marketing.

4 things b2b could adopt from b2c marketing

1. Marketing to People:

This translates to the personalisation of your marketing strategy that will tend to customers’ emotional and logical needs. B2C marketing for the longest time has honed the art of delivering personalized messages to individual prospects. While historically B2B marketing has been informational/educational akin to the needs of the several decision-makers involved. B2B prospects are nurtured with their need to research.

You’ll be surprised to know that adding a personal element to your interaction in your marketing promotes perceived brand value. In fact, B2B customers are 50% more likely to convert when they see personal value, and are 8x likely to pay a premium for a comparable service. The use of dynamic content that corresponds with a user’s needs on a website, and B2B email marketing to establish a personal tone, are some examples of personalisation. This isn’t to diminish the informational/professional element of B2B marketing but to add a personal touch to the same.

2. Building a Community Around the Brand:

From a business relationship to fans of the brand. Presumably, this is much harder for a B2B organization to achieve, while it’s second nature for most B2C brands. OnePlus for example built a community forum that gives users access to news, discussion and social features. This not only promotes the brand and its products but also allows for more customer engagement.

There are different channels through which B2B companies can build their communities. This can include creating a subreddit and uploading infographics on YouTube. Using these mediums could prove to be more useful than building your own forum thanks to the already well established B2B marketing communities within them. If you are keen on building one with a more tight-knit approach, consider forming a public discord server or a public slack channel.

When it comes to building a social media presence in B2B, having a social media presence alone won’t cut the mustard. Instead, a continual effort to build through customer engagement is key. B2C brands often create community posts and polls on Twitter, create short quizzes, answer queries, etc. This dynamic however is hard to build over the professional overtone, but adopting its practice should facilitate some creative and original content. It is also important to utilize a wide array of social media platforms, and not ones that might generate the most prospects.

Influencer marketing is something B2C marketing is all too familiar with. And for good reasons, people are more likely to purchase something with more credibility. But before you do so, you would have to sell the product to your influencer first, which involves a great deal of good faith and trust. The influencer marketing space in B2C is cataclysmically large, to scale the same for B2B would be pretty impractical. Instead, an affiliate program that incentivises existing customers to recommend the product or service to others. Even leaving reviews on authentic platforms like G2 increases the credibility of your brand by having other brands and marketing leaders vouch for it.

3. Buyer Personas and B2B Mobile Traffic:

Building a strong buyer persona is something B2B marketing could use to improve its content strategy and create more engaging content that addresses its challenges. This means understanding your target audience. In B2B this represents all the decision-makers involved, their pain points, goals and most importantly intent data. Research shows that B2B companies that utilize buyer personas in their content strategy perform better.

Speaking of buyer personas, it’s not unusual to expect a large portion of B2C buyers to use their mobile devices for research and queries. But what if I told you the use of mobile phones is gradually becoming the source of a lot of B2B search queries, over 50% of it to be precise. More buyers are using their phones for B2B research during work and leading organizations are generating 40% of revenue through it. Considering that mobile-first B2B generates higher engagement, site traffic, search queries and leads. Maybe it’s worth adopting from our B2C cousins.

4. Privacy and Privacy first marketing:

Becoming a privacy-first business is a big deal in this current digital climate. Given that the customer pool for the average B2C marketer is larger and its not so admirable track record with data security and privacy. More B2C marketers are becoming more proactive with their data and how they interact with it. This concerns B2B marketers as well, from a business perspective, data security is paramount. Educating yourself in B2C data security practices can be useful as most of the regulations governing these practices and the use of cookies stems from B2C practices in the past. To learn more about becoming a privacy-first business refer to this blog.

It's not hard to believe that the line between B2B and B2C marketing is getting blurry. At the very least they share the same goals. To generate as many leads and convert them. While contemporary B2B marketing adopts features of B2C marketing, the same could be said the other way around. Their culmination of experience in lead generation and conversion brings a lot to the table for the future of marketing methodology.

‍Digital marketing is effective,
result-oriented, and...expensive. 

Although by-the-book digital marketing channels contribute greatly to a company 's revenue and overall growth, performance marketing has emerged as a cost-effective alternative in the digital marketing space.

Performance marketing is a result-based marketing strategy wherein the advertising company pays only  for every successful transaction or interaction with their target audience. While this may seem like a no-brainer, utilizing performance-based methods can be an excellent way to ensure advertising efforts that translate to solid returns - increased customer engagement, reach on social media platforms, transactions on one's website, etc. 

This blog will serve as a handy guide for anyone looking to venture into performance-based marketing, its benefits, types, risks, figuring out whether it's a right fit for your brand and tools that can help with your performance marketing efforts in the future. 

What is Performance Marketing?

As opposed to traditional methods of advertising, such as putting up a billboard, or paying for ad space in a popular newspaper, performance marketing ensures that the advertiser pays only when a specific action is carried out by the target audience. 

For example, a brand may decide upon a featured ad on Instagram, paying a certain amount only when a user clicks on the post and is taken to the brand's official website. Not only does this model provide marketing efforts that are easy on the bank, but ensure easily measurable outcomes as well. 

A brand would find it much harder to track how many users viewed, engaged with, and responded to an ad in a newspaper. On the other hand, paying only when a user clicks on their ad helps form better, more actionable insights using various analytics tools and costs much, much less. 

Why is performance marketing preferred over other methods? 

As we've covered in earlier sections, one of the biggest advantages of performance marketing is its cost-effectiveness. Budgets for marketing can often be quite tight, and maximizing returns through advertising efforts is on the top of every marketer's list. 

Various types of performance marketing include Pay Per Click (PPC), Pay Per Impression, Pay Per Sale, and Pay Per Acquisition. The amount of flexibility these channels provide a brand, whether it's just starting or well-established, trumps other forms of marketing where cost may not necessarily set up your campaign for a higher ROI. 

Relatively Risk-Free 

When a brand invests before seeing results, there's always a factor of high risk and a low ROI. Questions like 

"What are the chances of this campaign running successfully?", "What if we do not receive our target CTR?" 

"Will we have to focus on other KPIs if our investment in this campaign is not returned well?"

are asked during all stages of campaign launches. However, utilizing channels that allow brands to pay only once a desired action is completed by the user eliminates a substantial amount of risk. 

Better, Clearer Insights 

Analytics tools track a wide range of customer insights, starting from their engagement with a brand touchpoint (such as a blog, social media ad, emails, etc).

Traditionally, marketing experts predict/expect a certain CTR, lead conversion, and, customer acquisition based on past campaigns and customer engagement. However, performance marketing takes the "guessing" out of campaign analytics, by showing clearer, more accurate insights of successful click-throughs, downloads, shares, sign-ups, and purchases. 

These insights are much more meaningful, as they provide actionable information on the brand's performance, based on the actions (such as signing up for a newsletter, downloading a product guide) the brand's needs and goals. 

How does performance marketing work? 

Now that we've covered the how's and why's, let's take a look at the various types of performance marketing, and how your brand can utilize these based on your campaign goals. 

PPC - Pay-Per-Click 

Perhaps the most popular type of performance marketing, PPC is a great way to ensure that your brand spends a certain amount only when your campaigns/ads receive a click from the user, taking them to your target landing page.

A great example of PPC is paid ads on search engines such as Google. Once you bid for your ad campaign to show up in search results every time your target audience searches for a relevant keyword, you end up paying only when they click on your ad - an extremely cost-effective method to ensure you only pay for genuine, promising leads. 

PPM - Pay-Per-Impression 

The number of impressions your ad has is the number of views it has gained on a platform, such as Instagram or Youtube. CPM involves a brand paying a certain base rate for, say, every 100 views. So, if your campaign received 500 views, you only pay an amount equal to your base rate x 5. 

PPL - Pay-Per-Lead, PPS - Pay-Per-Sale & PPA - Pay-Per-Acquisition 

In CPL, an advertiser pays only when an action that helps convert a viewer into a lead is undertaken, for example, paying every time a person signs up for a product demo, or a consultancy call with your brand.

Cost-Per-Sale is used most widely in affiliate marketing, when the advertiser pays only when a sale was carried out successfully, after converting a consumer into a lead. Often, influencers and affiliate marketers use referral codes to direct their audience to the company's website, receiving a certain percentage of profits gained through sales. 

 CPA, on the other hand, is more generalized in nature. The company pays when any desired action is carried out by the consumer, be it visiting the landing page, sharing their email ID, signing up for event reminders, etc. 

Where Can You Use Performance Marketing? 

Digital marketing is an extremely diverse space, with efforts being distributed across social media platforms, search engines, and emails. Performance marketing, too, can be utilized across a wide range of digital mediums to ensure your marketing campaign reaches your target audience quickly, effectively, and can translate into long-term gains for your growth. 

Here are a few niche spots you can target with the strategies mentioned above - 

Affiliate Marketing 

Got a product or service to sell? Bring in affiliates to help spread the word! Affiliate marketing is a fast-growing method that ensures better reach, boosted sales, as well as higher customer engagement due to local and personalized reach. Establishing a PPS framework with affiliates is the best way to move forward. 

Social Media 

With over 58.4% of the world's population on social media, these platforms are a goldmine for boosting brand reach. Designing solid social media strategies on popular platforms such as Instagram, Pinterest, Facebook and TikTok and directing interested users to a relevant campaign can do wonders for your brand. What's more, you only pay when a user completes an action you want them to carry out - visiting your website, downloading your newsletter, etc! 

Targeting Search Engine Results 

For search engine marketing, there's two ways your brand can gain more visibility - 

• Organic efforts (SEO) and 
• Paid ads and features 

Search Engine Optimization, or SEO, is a tool that you can use as part of your content strategy to boost organic growth over time. Targeting the right keywords for your brand, including them in your content, metadata, headings, and descriptions can help your website rank higher every time a user searches for a relevant keyword or phrase. 

 On the other hand, designing ad campaigns on search engines such as Google help drive greater traffic to your website due to its high visibility. To top that, ad campaigns are usually based on a PPC model, so that means you pay a certain amount only when a user clicks on your ad! 

Things to keep in mind 

While performance marketing may seem like the solution to all of your marketing issues, keep in mind that not all of your campaigns should be focused on performance-based models. Clearly defining your company's overall and campaign goals is essential before charting out a marketing strategy. 

Here are a few questions you should ask yourself before venturing into performance marketing - 

• What are my goals for this campaign? 
• Is it to drive more user traffic? 
• Is it to rank higher on search engine results? 
• Is it to boost sales of a certain product/service? 
• How much risk am I willing to take with this campaign?
• Who is my target audience? What are their needs? 
• Is my campaign addressing their needs or simply promoting a product or service? 

In conclusion...

The world of digital marketing can be a tricky one to navigate, especially with the endless number of solutions that can be applied to a brand's ad efforts. However, performance marketing is emerging as a successful, popular, and easy-on-the-budget option for most business models and ad campaigns. 

Tools like Affise, AnyTrack, and ClickMeter are popular tools that can help you measure, inspect, and manage your performance-based efforts across various platforms. Alongside these tools, utilizing methods such as PPC, PPM, PPA, and PPS is the boost your brand needs this year! 

‍With GA4 here to stay, here’s why you might want to leave

[July 5th 2023 Update] As of this month, GA4 has been sunsetted. What's more? Sweden has recently announced a comprehensive ban of Google Analytics due to security concerns. The Swedish Authority for Privacy Protection has cautioned users against the use of GA as a result of privacy risks posed by the U.S. government. This makes Sweden one of several European nations to have elected to ban Google Analytics in recent months.

It’s official — on July 1st, 2023, GA4 will permanently replace Universal Analytics (GA3) as Google’s primary marketing analytics platform. While ga4 vs universal analytics (ua) is still hotly  debated, the general verdict emerging within the marketing community is that ga4 falls short in several, fundamental aspects. Criticism ranges from ga4’s exceptionally unintuitive UI to limitations around ga4 events, event parameters, and reporting mechanisms. The following article lists out a few of these major drawbacks to highlight why it may be time for B2B marketers to consider ga4 alternatives. 

I usually can find my way round any piece of software quickly. But Google Analytics 4 is making me cry...

I've never seen a tool upgrade that made simple things sooo complicated :face_palm: Non-tech business owners were already struggling to use it. But now they have NO chance.

Gill Andrews (@StoriesWithGill)

GA4 migration challenges

The most pressing issue with migrating to GA4 is that the platform is not ready for independent use as of yet. Several bugs continue to persist, third-party integrations are scarce, and many features, including core ones like internal filtering, continue to remain under development. To be fair, ga4 is likely to squash these issues by the time it's standardized in 2023. But at the moment, ga4 is a half baked product. 

How to set-up GA4? Well, the logistics of migrating to ga4 isn’t all that straightforward either. While former universal analytics users have the option to upgrade for free, this facility is not available for all ua properties. Depending on your Google Tag Manager implementation, setting-up GA4 can take significant time and effort (depending on developer bandwidth) — in some cases, as long as a month!

Marketing analytics on GA4

Missing metrics and reports on GA4

A big change from UA to ga4 is the shift away from sessions and pageviews. Hit types like page views, social, transaction, use-timing, and more have been consolidated into a single measurement property on ga4 — events. Familiar metrics like average session duration and bounce rate have been stripped as well. The latter is an especially jaring loss because it’s a valuable metric for marketers to understand and compare landing page performance.

Standard reports have also taken a hit in google analytics update from UA to ga4. For instance, acquisition reporting on UA had as many as 30 standard reporting techniques. This included useful features such as traffic acquisition reports and source/medium reports. Unfortunately, ga4 has adopted only 10% (just 3) of its predecessors standard reports! One explanation for this is that ga4 is transitioning from a full fledged marketing analytics platform to a solution that enables you to capture and transport data elsewhere for further analysis. 

Conversion tracking on GA4

Universal analytics offered 4 types of goals — session duration, page/sessions, destination, and event. Conversion goals could easily be configured, for example, a “thank you” page could be tagged as the destination to measure form-fill conversions, in a matter of seconds. Because ga4 misses out on this “destination” goal type, ga4 requires tedious, manual GTM configurations to set-up “form-fills” as a conversion goal. In fact, Zack Duncan from the Root and Branch Group found that it takes around 16 minutes (along with adequate knowledge of GTM) to configure submission tracking on GA4 (as compared to a minute on UA). This is a major limitation for B2B SaaS websites and marketers as a significant proportion of leads come through demo form fills.

Event collection on GA4

Other Ga4 mechanisms have also faced significant backlash for a couple of reasons. Let’s start with event collection limits. As a rule, ga4 will not log events, event parameters, and user properties that exceed these limits: 

• Distinctly named events: 500 per app instance 
• Event parameters per event: 25 event parameters only
• User properties: 25 properties only

While these limits may suffice for early-stage teams, event collection on ga4 will almost certainly become an issue once the organizations starts to scale and garner complex events on relatively high-traffic websites.

Character limits on GA4

What’s especially concerning is that on ga4, distinctly named events and user properties can not be deleted/updated if you’re close to hitting their limits. In addition, ga4 heavily restricts character length on event and user names and values. For example, ga4 will truncate page names to a maximum of 300 characters. So, if your landing page has a url longer than 300 characters (which is far from uncommon), it will consider only the first 300 characters and perform attribution and analytics based on that. This could also mean that the entirety of the UTM may not be sent to google analytics servers, which in turn means a significant loss in data.

Data sampling and Processing time on GA4

Credit where credit is due — ga4 has taken a big step in the right direction by eliminating data sampling for standard reports. The keyword here, however, is standard. Advanced reporting (explore, advertising, configure) on ga4 continues to sample data under certain conditions. These advanced reports include core techniques like funnel exploration, path exploration, user explorer and more.

A drawback of unsampled data analytics on ga4 is the processing time. Standard ga4 claims up to 24 hours of processing time for intraday reporting and as much as 48 hours for complex features like multi-channels funnels and attribution modeling. To put this in perspective, Factors.ai delivers standard reports near instantly and will require at most 24 hours (half that of ga4!) for multi-touch attribution reporting.

While on the topic of data, it’s worth mentioning that ga4 offers data-retention for up to 14 months only. What’s more? XL properties are limited to a measly 2 months! This can be of great hindrance to B2B SaaS marketing analytics — wherein customer journeys can easily stretch across a couple of years. 

Custom events, properties, and dimensions on GA4

As of today, GA4 supports only 2 scopes for custom dimensions: event scopes and user scopes. This is two less than UA’s custom scopes which covered session and product dimensions as well. What’s worse is that the pair of custom dimensions offered on GA4 are heavily limited (even with GA360!). Here’s how the limits break down for standard GA4:

• Event-scoped custom dimensions: Max 50
• User-scoped custom dimensions: Max 25
• Custom metrics: Max 50

If you reach the ceiling on these custom dimensions, unfortunately your only option on ga4 is to archive infrequently used dimensions and hope for the best.

And there you have it…

This article explicitly covers a non-exhaustive list of shortcomings with GA4. Other concerns include useability, privacy-risks, lack of third-party integrations, and challenges at scale. While Google Analytics has dominated the marketing and web analytics space for years now (mostly because it’s a free tool), its limitations are starting to catch up with it. With dozens of robust Google Analytics alternatives emerging from the market, now is the time to replace ga. 

Factors is an end-to-end marketing analytics and revenue attribution platform that goes above and beyond the likes of Google Analytics to help you make sense of (and optimize) your marketing efforts. Here’s how Factors compare to Google Analytics. 

Interested in learning more? Book a personalized demo here! 

The following blog is an overview of account scoring. It goes over the basic steps in creating a scoring scheme as well as the various functions of an ICP (Ideal Client Profile). It also distinguishes account scoring from ABM (Account-Based Marketing) and assesses how lead scoring and account scoring deal with different B2B clients.

Catch our previous piece on lead scoring models explained here!

What is account scoring, and how is it different from account based marketing?

You might have heard that account scoring is somewhat analogous to ABM (Account-Based Marketing). This isn’t far from the truth. Think of account scoring more as a means to improving ABM. In that sense, they are consubstantial. ABM is a broader approach to marketing that targets key accounts or accounts that are most likely to convert and generate the most revenue. This is based on using an ICP (Ideal Client Profiles) which states the attributes of those target accounts. ABM also deals with compartmentalizing those key accounts, designing the method of engagement, and collaborating with other departments.

Meanwhile, account scoring is a method of ranking and sorting your target accounts based on a scoring scheme. Just like in ABM, account scoring uses an ICP as a filter to identify your target accounts. By scoring your target accounts you can better ascertain the value of organizations, on which you can expend your limited resources on. Account scoring is comprehensive with its scoring schemes by prioritizing unique attributes of target accounts.

Steps to create account scoring:

‍1) Ideal Client Profile: Your ICP in account scoring has two functions. The first is to use your ICP to make target accounts or rather filter out a range of target accounts before scoring them. The second function of ICP acts like an explicit scoring model as in lead scoring. This means using your ICP as a benchmark while scoring organizational traits, like the size of the company, ACV, location, etc. This becomes an inevitable part of your scoring scheme.

2) Creating a Scoring Scheme: A scoring scheme is nothing but the basis of assigning a score to a target account. As mentioned in the previous step, your ICP has the role of designing your explicit scoring. With that sorted, you can establish some implicit scoring criteria. Such as rewarding points based on email engagement, content download, and web analytics. For example, an organization visiting a review page could earn 3 points, while traffic generated through PPC could earn 7 points. The value of certain touch points and engagements can be determined by using a revenue attribution tool.

3) Customisation: A scoring scheme is never linear. All elements within a scheme might not apply to every organization. Different organizations and stakeholders might have different uses for your services and different valuations for their touch points. Hence, it is important to measure the relative impact of the scoring scheme on your target accounts. It is also crucial to revise your ICP, rearrange their permutations, create several ICPs, and compare them.

Account scoring vs lead scoring

One could argue that both these scoring methods are somewhat similar. Both their scoring models have an implicit and explicit element to them. So, is it just a matter of what they’re called? The most important distinction here is that account scoring deals with organizations while lead scoring deals with individual leads.

Account scoring views a client as an organization with several decision makers involved. While lead scoring is better suited for dealing with a single decision maker. This is why lead scoring is the better choice for clients with a lower ACV, this implies a low level of decision making involved, with only one or few decision makers. And because of its individualistic nature, lead scoring has a stronger emphasis on engagement.

Account scoring on the other hand is better suited for high ACV organizations with more decision makers. This necessitates the need to create key accounts for an organization rather than scrutinizing an individual lead. It also works better with ABM and account-based engagements. The use of ICP has more prominence in organizations and takes the number of stakeholders and ACV into account.

Customer success lends to B2B business success

There’s no two ways about it, customer success is crucial to B2B success. Especially because  it is 5 to 25 times more expensive to acquire a new customer than it is to retain existing ones. Accordingly, quarterly business reviews or qbrs have emerged as a pragmatic solution to the challenge of customer churn in modern B2B organizations.

What is a quarterly business review?

A quarterly business review (qbr) is a strategic review meeting with your clients and their executives that occurs (usually) every quarter. In this meeting, which is usually led by the customer success team and their managers, businesses review the efficacy of their services on the client’s business, discuss any improvements, future plans, redress client concerns, present the business’s progress, and all in all perpetuate good customer relationships.

A productive QBR is designed with the client’s goals in mind, and to strategically align them with the customer success team’s goals. The most important aspect of a qbr is to open a dialogue between business and clients, and not to make a sales pitch to them. emphasizing too much on presenting the business’s progress will overshadow that agenda.

Setting up an effective quarterly business review (QBR):

1) Review frequency: though present in the name, a quarterly business review does not have to occur every quarter. Sometimes, businesses might require a longer time interval between meetings to ensure adequate value. One of the reasons could be that your business might require more time to produce quality content and data for effective reviews. Another reason may be the logistical challenges in arranging meetings with the right audience/stakeholders required for a meeting. If a business cannot produce consequential insights for a review, then there is no reason to hold one.

2) Meeting agenda: creating an agenda forms a structure for your review, upon which your clients can base their expectations and questions on. A missing agenda risks your meeting attendance.A well-planned agenda that is organized and ahead of time for the clients is an essential component of a QBR. The contents of an agenda might include:

• Previously discussed plans
• Innovations and improvements to product/services
• Previewing upcoming products
• Customers’ future business plans
• Business near future roadmap
• Reporting progress, roi and other analytics
• Redressal of challenges

3) Transparency: as discussed in the last point, having your attendees pre-approve your agenda before the review shows a great deal of transparency and builds trust with your customers. But besides that, being honest about your failures and shortfalls shows your business’s willingness to improve. At the end of the day, the goal of these reviews is to build your relationship with your clients, and sincerity goes a long way.

4) Presenting the data: when it comes to presenting your business’s progress, showcasing your ROI could be at the cornerstone. Highlighting your ROI shows growth and the value retained in procuring your business’s services. It's also the perfect metric to underscore your track record & other progress in conjunction with your future goals.

Outside of ROI, presenting benchmark data is vastly appealing to your clients as they’re interested in learning where your business places itself among competitors every quarter. specific metrics that clients might require based on questions and the discussion from previous quarters also come in handy.

5) Progress and future QBRs: After highlighting your business’s progress, putting forward the plans for your next qbr is a great segue. This could also be a good time to pitch in some future milestones, along with previews of new products and services. This is even a good opportunity to present innovations at a conceptual stage. Just remember to seek your client’s approval for your plans and future changes.

Common QBR mistakes:

• Lacking a plan: QBRs are value-added reviews. The most important element here is time, the review cannot afford to be haphazard, and it must have clear objectives that allow for value to be transferred. The quality of the content & discussions need to leave the attendees, and especially the executives, with more than what they had before the review. The main focus of a QBR is not to just present reports, but to have them done ahead of time and to emphasize on business value.

• Lacking feedback: The bottom line isn’t that you’re listening to feedback during a review, but that you are not asking for more. Being proactive, and presenting the chance for your clients to provide valuable feedback is an opportunity lost if you don’t make use of it. running a customer satisfaction survey or having a q&a after every review is an example of being proactive about feedback. 
• Beating around the bush: keep your meetings brief and avoid fluff in the form of irrelevant data and discussions. Most qbr meetings are scheduled to last anywhere from 30 to 90 minutes. This isn’t a lot of time once you have allotted a good chunk of it for a q&a. Ensure only material points are being discussed, and don’t forget to schedule and plan out the next meeting.

Planning a QBR comes with its own host of problems. distinguishing your goals from your client’s. managing different expectations, adding value to your reviews and so much more. but to truly win over your clients, you would have to go over and beyond. go as far as asking your clients what it would take for them to opt out, for them to choose another service. and while most businesses wouldn’t ask that, you should, because your customer is another business’s prospect and if you don’t stick your neck out, your competitors will

Why did Linkedin acquire Oribi?

On March 31st 2022, Linkedin announced its acquisition of Oribi — an Israel-based marketing analytics company, for over $80 million. Oribi was a marketing analytics platform that offers seamless integration and automated event tracking for your website without the need for coding. They provide a user-friendly platform that combines several conversion rate optimization (CRO) features, including customer journey funnels and event correlations, making it easy for users to access and utilize these tools. 

 An agreement was reached with Oribi CEO, Iris Shoor, after several conversations about product and value alignment. Linkedin’s purchase of Oribi is part of a larger strategy to expand features across Linkedin Marketing Services (LMS). LMS includes a range of strategies, techniques and tools used to promote advertisements, profiles and other businesses on LinkedIn. This helps advertising firms and recruiters to get actionable insights into their posts and advertisements. 

With this acquisition LinkedIn aims to position itself strongly in the advertising and marketing analytics domain. With a 43% growth in the marketing service revenue on yearly basis, LinkedIn wants to grab on to the momentum of the growth trajectory of the marketing revenue. It aims to provide its users with keen insights with more data analytics and attribution in order to stronghold itself as a competitor to Google Ads services. 

But what are the implications of this acquisition? and how does this affect former-Oribi customers? Let’s find out.

“Understanding which channels and messages have the greatest impact on the decision to take a desired step, such as a buyer requesting a product demo or a job seeker applying to a job posting, is critical to the effectiveness of any marketing campaign. Through the integration of Oribi’s technology into our marketing solutions platform, our customers will benefit from enhanced campaign attribution to optimize the ROI of their advertising strategies” - Tomer Cohen, CPO, LinkedIn

How will Linkedin use Oribi’s technology? 

As previously mentioned, Linkedin acquired Oribi with the intention of expanding its LMS portfolio with industry-leading marketing and web analytics software. In particular, Linkedin was expected to employ Oribi to improve LMS insights tag implementation, drive audience insights for retargeting and CRO, and create customer journey funnels for Linkedin campaigns. Campaign attribution and ROI reporting are other Oribi use-cases Linkedin seeks to leverage for LMS.

As part of the agreement, Linkedin  opened its very first office in Tel Aviv. The majority of the Oribi team has already joined Linkedin’s LMS division as well.  LinkedIn’s action also came with a series of layoffs. According to some reports, 17 Oribi employees working in customer facing verticals(sales, marketing etc) were fired post acquisition.

“Oribi’s team brings deep analytics expertise that will help us accelerate the capabilities of our attribution technology across our lines of business – from helping a marketer find better leads to a recruiter identifying the right candidates. The acquisition will expand our international presence so we can continue delivering products that meet the evolving needs of our global customers and members.” - Tomer Cohen, CPO, LinkedIn

What does Linkedin’s acquisition of Oribi mean for customer data?

A couple of things. First, any data captured following Oribi’s integration remains in the control of customers and adheres to all commitments set by Linkedin’s standard ads agreement. This means that LinkedIn will not use, edit or tarnish the data already captured by Oribi for its existing users. Second, Linkedin will not be combining legacy personal data between Oribi and Linkedin. This means that the data captured by Oribi prior to the acquisition will not be used by LinkedIn in any way, therefore, the existing customers data will not be scrutinized by LinkedIn post integration.

Finally, there are no plans for Linkedin to alter the data it currently collects from users — simply to enhance existing data using Oribi’s technology. This implies that LinkedIn will not change or update its data collection policy from its users post integration with Oribi. Therefore, LinkedIn users should not be worried about collection of additional data points to enhance Oribi’s functionality. 

What does Linkedin’s acquisition of Oribi mean for former Oribi users?

According to several reports, Oribi shut down services and canceled customer contracts just weeks after the agreement was reached. Based on conversations with former Oribi-users, its revealed that Oribi has offered its customers a couple of options: 

1. Try out Oribi/LMS’s early-stage pilot program 
2. Switch to an alternate marketing/web analytics solution

The problem with the first option is that as a result of Linkedin’s acquisition, the pilot program is heavily limited. Integrations with third-party ad platforms like Google and Facebook look likely to be restricted as well. Therefore, the customers will not be able to get the ultimate benefit of marketing analytics, and integration features post acquisition. Accordingly, option 2 is the popular choice. Especially since historical data will not be preserved, now seems to be the best time to switch to an alternative solution for Oribi.

‍Best Oribi Alternatives in 2023

Since the acquisition of Oribi by LinkedIn, significant changes have taken place. Although it was anticipated that LinkedIn would leverage Oribi's capabilities to improve its marketing analytics, many users believe that the acquisition did not turn out to be favorable for Oribi.

Many users were not happy with acquisition, as they anticipated a large number of Oribi features to be eliminated post acquisition. Therefore, many Oribi customers are out scouting for viable alternatives for their needs.

There are a host of platforms to consider for replacing Oribi including Factors, Heap (which is a powerful solution, but suited more for product analytics), Wicked Reports, and Plausible. 

Let's compare some of the top alternatives to Oribi and see how they fare in terms of their features (pros and cons), pricing, integrations and user reviews.

1. Factors.ai

Fcators.ai is a marketing analytics tool which specializes in multi touch attribution with a focus on account based analytics and visitor identification.

Oribi does not offer the concept of dashboarding, making it difficult to group and visualize reports efficiently. Factors provides customizable dashboards where all reports are conveniently organized and displayed, simplifying the process of data grouping and visualization. It allows users to consolidate essential data in a single location, enabling easy tracking, analysis, and generation of insights to optimize marketing campaigns effectively.

Factors offers account-based analytics which includes campaign analytics, website analytics, and funnel analytics.  With Factors, marketers can enhance their understanding and optimization of website conversions with automated tracking of buttons, detailed page analytics, access to unsampled data, and the ability to track custom domains. Factors provides end-to-end journey analysis with Funnels, letting the user add as many filters as they like to easily customize their data and dashboards.

What’s more is that Factors consolidates various metrics such as CPC, CTR, ROI, impressions, and more at different levels like channels, campaigns, ad groups, and keywords, enabling more detailed data-driven marketing strategies, this was not possible in Oribi.

Moreover, Oribi has limited integration with HubSpot, only allowing the push of web data into the CRM. In contrast, Factors integrates with both HubSpot and SalesForce, enabling the connection of campaign and web data with contact data, offline events, and revenue metrics from the CRM. This integration empowers comprehensive analysis and attribution throughout the customer journey.

Factors can be set up within 30 minutes and offers no-code integrations with ad platforms, CRMs, MAPs, and CDPs.

Both Oribi and Factors deliver intuitive web analytics, CRO, attribution, and funnels. On top of this, Factors also provides end-to-end customer journey mapping across campaigns, web, & CRMs. You can learn more about how Factors compares against Oribi here. 

PROS:

• Unlike Oribi which only provided website attribution, Factors provide attribution at every relevant touchpoint from ads and website interaction to offline interaction using CRM integration. With customizable reports across channels, campaigns, and keywords, Factors can be moulded to any need which the user might have.
• Factors has an impeccable 64% visitor identification rate which is the highest in this category.. Along With its robust visitor identification feature complemented by multi-touch attribution, you can perform various attributions including offline touchpoints to identify the various sources from where visitors come to your website.
• Factors is now the official Marketing Partner of LinkedIn. With this collaboration, the users can get complete information about who is viewing Linkedin ads, clicking on them, and how this leads to conversions. With this partnership, users can optimize their campaigns with AI driven insights for all of their marketing efforts..

CONS:

• Factors cannot automatically send data back into Hubspot or Google Analytics like Oribi. Therefore, it may not be a good fit for you if you are looking for data orchestration rather than analytics.
• Factors does not support integration with ActiveCampaign, Mailchimp, and Klaviyo. Therefore, the user may miss out on the use cases relevant to these integrations

Integrations:

• Google Search Console
• Google Ads
• Facebook Ads
• LinkedIn Ads
• Hubspot 
• Salesforce
• Clearbit
• Segment

Pricing:

Factors offers a free 14 day trial with no credit card requirement. Visitor Identification and Website Analytics plans start at 99/month, while it has a separate pricing plan for Multi-Touch Attribution starting at $399/month.

Reviews:

2.  Plausible Analytics

Plausible Analytics is a  cookieless web analytics tool designed specifically for a wide range of businesses including small and medium-sized enterprises (SMEs), startups, content creators, bloggers, and e-commerce websites.. As an open-source tool, Plausible offers a transparent and customizable solution that empowers businesses to track website performance without compromising user privacy. It offers intuitive data analytics with traffic segmentation, shareable dashboard and real time notifications. Plausible aims to provide simple web analytics at a glance without any complex layering of data with menus, and complex reports. Instead of tracking every imaginable metric, Plausible focuses only on relevant and most important data points.  Like Oribi, Plausible provides intuitive data analytics features which are compressed in a 1KB script.

Plausible’s script size is smaller than 1KB, ensuring that website loading time is reduced. With a script size which is 45 times smaller than Google analytics, plausible occupies less space and gets easily installed.

PROS:

• One of the standout features of Plausible Analytics is its incredibly lightweight script, clocking in at less than 1KB. This means that implementing the tool won't slow down your website's loading time, ensuring a seamless user experience for your visitors. 
•  Plausible complies with GDPR, CCPA, and PECR.. It offers real time slack and email updates which are customizable based on the user’s needs.

CONS:

• Plausible does not provide multi touch attribution but only last click attribution. This leaves you unsure of where the leads actually come from. 
• Since Plausible Analytics does not collect or store personally identifiable information (PII) and avoids the use of cookies, it means they do not retain historical data beyond a 30-day period. This could pose a challenge if your tasks involve long-term data analysis or trend tracking, as the limited data retention may affect your ability to derive insights and perform comprehensive analysis

Integrations

• Bubble.io
• Carrd
• Hubspot
• Google Data Studio
• Google Search Console
• Notion
• Wordpress

Pricing

The tool provides a free trial, and the paid plans start from just $9 per month for 10K visitors. Furthermore, users can get a 2-month free subscription if they pay annually.

Reviews

3. Heap

Heap is an analytics tool that automatically captures, tracks, and visualizes visitor engagement with the website to provide actionable insights. Heap collects data and collates it into easy to read graphs and funnels.Heap focuses on enhancing customer engagement and tracking their activity throughout their journey with a brand. Heap offers a diverse array of capabilities, like automatic event tracking, retroactive data capture, and real-time reporting. It empowers businesses to segment their data based on users, sessions, and events, simplifying the process of identifying trends and patterns within the data.  For Oribi users, Heap could be a good fit since it provides customers with funnels, real time reporting, and a host of data visualization features. 

PROS:

• Heap offrs intuitive and customizable  dashboards to coordinate important metrics for the business and help drive insight driven actions. It allows businesses to segment their data by users, sessions, and events, making it easier to identify trends and patterns.  
• Heap provides user segmentation, which helps categorize users based on their characteristics and behavior. This feature allows businesses to track users retroactively, gaining insights into their past interactions and activities. With user segmentation, companies can better understand their audience and tailor their strategies to meet specific user needs.
• With the user timeline feature, Heap enables marketers to see detailed user level data as to how each user interacts with the website/app. The timeline of this activity can be adjusted from the last 7 days to the date the user first interacted with the website/app. 

CONS:

• Heap occupies a large amount of space due to its many features and comprehensive data storage features.. When you have a lot of data stored, it becomes more challenging to calculate the costs associated with data privacy and protection, storage and archiving, and regularly backing up the data. The complexity increases as the amount of data grows, making it important to carefully manage and allocate resources to ensure data security and accessibility.
• Heap only focuses on the website traffic, user activity on the particular site and conversions. It does not factor in the role of paid ads, organic reach on search engines and other touchpoints. Here is where a tool like Factors comes into play as it gives you a complete and in depth overview of the data attribution and visitor identification across multiple touchpoints.

Integrations:

• Shopify
• FullStory
• Clearbit
• RedShift
• Eloqua
• Hubspot
• Salesforce

Pricing 

The tool provides a free trial and a free package for up to 10K monthly sessions. The growth package is priced at $3600/YEAR for 3OOk sessions per year.

Reviews

4. Wicked Reports

Wicked Reports is a marketing attribution platform with a wide assortment of campaign analytics features. Some of its unique features include the ability to include/exclude subscription revenue, distinguish new sales from recurring sales revenue, and new leads from re opt-ins. 

Attribution in Wicked Reports is its standout feature, primarily used for generating ROI reports. Users can pick from various attribution models provided by this platform like, linear attribution, last click, first click attribution, full impact attribution etc. Wicked Reports also generates insights into customer lifetime value and cohort analysis.

Pro:

• Wicked Reports offers cohort analysis capabilities, allowing you to analyze the behavior and performance of specific groups of customers over time. The platform helps in the visual representation of the monetary value and ROI of the customer, illustrating their profitability and financial performance over time..

CONS:

• Wicked Reports cannot be used to visualize customer funnel journeys. This means that marketers will not be able to locate where leads are lost.   Customizing and visualizing of funnels is possible with tools like Factors.ai.
• Wicked Reports primarily focuses on marketing attribution rather than web-level attribution. It specializes in attributing marketing efforts to revenue and ROI, helping marketers understand the impact of their various marketing channels and campaigns. However, when it comes to granular web-level attribution, such as tracking specific user actions on a website, Wicked Reports may not provide extensive capabilities in that area

Integration

• Hubspot
• Mail Chimps
• Shopify
• Google Ads
• Facebook Ads
• Snapchat
• Paypal

Pricing

Reviews

In conclusion…

LinkedIn’s acquisition of Oribi came at a crucial time for the marketing analytics and attribution space. With a keen focus on positioning itself as a strong rival to Google Ads services, LinkedIn aims to utilize the marketing analytics and attribution features offered by Oribi. LinkedIn wants to focus on  its campaign manager which has now become more and more relevant to analyze marketing campaigns.

That said, Oribi can definitely improve its interface and analytics capabilities especially with the continued support of Microsoft. With the acquisition now completed, LinkedIn now has in its coffers a host of features to drive its marketing analysis and attribution arm. As a result, LinkedIn will now be able to offer recruiters and advertisers complete analytics of their ads and posts fueled by AI-driven insights.

Now, more than ever, marketers feel the need and importance of monitoring their efforts and making data-driven decisions to ensure they’re getting the most bang for their buck. The role of marketing analytics will only become increasingly important as even conventionally offline events like seminars and conferences turn digital.

Although the acquisition proved fruitful for LinkedIn and its marketing analytics tool, existing customers did not like it as much. Post acquisition, Oribi shut down its customer-facing vertical, culling out numerous features and also fired customer-facing employees.The existing employees of Oribi especially the sales and marketing vertical had to bear the brunt. Additionally, the existing customers had to venture out in search of alternatives to replace Oribi, which resulted in additional costs, and wastage of time.

The search for an Oribi alternative ends here with Factors. Factors has proven to be a highly effective marketing analytics and attribution platform for B2B marketers. Try it for free or schedule a personalized demo to witness its impact on your campaigns and website conversions today! 

FAQ:

• Why did LinkedIn acquire Oribi?

With Oribi’s acquisition, LinkedIn was looking forward to optimizing its marketing and advertising service. LinkedIn aimed to solidify its global presence by providing marketers and recruiters a keen insight into their campaigns. According to Tim Cohen (Chief Product Officer at LinkedIn), marketing services grew about 43% on a yearly basis, with Oribi in its coffers, LinkedIn aims to drive this growth potential and position itself as a reliable source of advertising and marketing services.

Furthermore, LinkedIn aims to position itself as a firm competitor against Google's ads and marketing service. 

• What are the best Oribi alternatives?

Some of the best Oribi alternatives for 2023 are Factors.ai, Heap, Plausible Analytics,and Wicked Reports. Some other platforms to look out for are Mixpanel, Amplitude and Fullstory. Oribi carved out a strong position in this market due to its no code and easy to use market attribution feature which housed loads of CRO features. One should look out for relevant attribution services with an easy to use interface in order to match the experience of Oribi.

What do you do when you’re stuck nurturing countless leads that drive few conversions? Lead scoring has emerged as an effective solution forthis customer conversion challenge. Studies show that B2B organizations that utilize lead scoring realize a 77% increase in lead generation ROI compared to those that don't. If this piques your interest, know that scoring your leads and determining a lead scoring model is not a cut and dry process. The following post explains what lead scoring is and explores some commonly used lead scoring models.

What Is lead scoring?

Lead scoring is the procedure of quantifying the conduciveness of a lead generated by a business. To put it simply, it is used to determine if a lead is more likely to convert or not by assigning scores to the leads. By doing so, you ensure that both your marketing and sales teams are seeding the right prospects, all while getting to understand who your ideal lead is in the process.

So far, it seems simple right? Well, scoring leads is not all black and white. Figuring out your buyer persona is a multifaceted challenge. It not only requires a boatload of data but constant revisions and maintenance over time as well.

To help with that, here is how you build your lead scoring model:

Determining lead scores

First, we need to figure out the criteria for scoring, and how many points to reward or deduct for each criterion. Here are a couple of steps to establish that:

1)     Picking your KPIs and Traits: The first step in lead scoring is selecting what you need to be judging. This involves the KPIs (key performance indicators) and common traits of leads that convert. An example of this would be that an important KPI is the number of views on the review page for a product. And a common trait could be a particular company size.

2)     Assigning the Value: It is important to understand which traits are more significant than others — like the lead’s company size over the industry. This way you can reward certain traits higher than others. You should even determine the points to be rewarded per trait — which company size converts the most and which ones convert the least, etc. You can do this by calculating the conversion rates of the leads with different levels of the same trait and comparing them to the average. The same can be done for KPIs as well.

With all these in place, you can now determine the score for each lead attribute. Remember that you must never only rely on one attribute to score your leads. The more the merrier, as the following lead scoring models deal with a wide variety of data.

Lead scoring models

A lead scoring model is nothing but the basis of evaluation for your scoring or the system on which it is predicated. With that said here are some common lead scoring models:

1) Implicit Scoring (Activity/Engagement): Implicit scoring is used to grade leads based on their level of activity and engagement with the business, its brand and its content. It utilizes a lot of tracking data across several platforms and compared to explicit scoring it is a continual process. Here are some examples of implicit scoring:

• Number of webpage visits or leads that visited the pricing page.
• Content engagement, including views, downloads, etc.
• Email engagement, email click-through rate and bounce rate.
• Social media interactions, involving likes, comments, followers, etc.
• Leads that requested for product demos and free trials.
• Leads that attended webinars.
• Form submissions, and more

2) Explicit Scoring (Suitability): Explicit scoring is used to evaluate a lead based on their business-related profile like the lead’s company size and job title. This information is used to determine the suitability of your lead’s business profile to that of a lead that converts. Explicit scoring is more commonly used in B2B interactions, given the importance of assessing the companies they deal with. Here are some examples of explicit scoring:

• Company size, which can allude to how many decision-makers are involved in the buying decision.
• Job titles that are awarded different points depending on the level of influence.
• The company’s revenue could help identify companies that are more in line with your average contract value.
• The lead’s company industry.
• The location and other demographics of the lead.

3) Matrix (Combination of Implicit and Explicit Scoring): This model is called a matrix model because it uses an incidence matrix combination of implicit and explicit scoring. This means that we evaluate a lead based on combinations of implicit and explicit traits at varying degrees. For example: A lead that is considered highly suitable based on explicit business profile traits like company size and industry can be scored poorly due to its low activity and engagement levels. The same could be said about a lead with high activity but low suitability.

The importance of both these dimensions varies based on your ideal client profile (ICP). The use of this matrix model, including models with other dimensions, are quite common in lead scoring solutions used today. Like Silverpop’s scoring system.

4) Negative Scoring: A negative scoring model implements a deduction of points to your lead scores based on unfavorable interactions and intentions. Negative scoring involves a multitude of aspects. From the low levels of activity or interest found in leads, to prospects consuming your content for all the wrong reasons. The biggest advantage of implementing this model is that it avoids inflating a lead’s score. And allows your sales team to focus more on better leads. Here are some examples of negative scoring:

• Inactive or stagnant leads that have not interacted with the business in a while.
• Leads that unsubscribe to your company newsletter.
• Rival companies researching your company.
•  Visitors that consume your content with no interest in the product, but for other reasons (academic/employment)

Regardless of which model you pick, you’re more likely to adopt a combination of these models so long as it meets your scoring requirements. And as long as you fine-tune your method in conjunction with newer customer data, you can ensure that your lead scores will always stay credible.

Oribi vs Wicked Reports

With Oribi discontinued, B2B and E-commerce teams are on the hunt for alternate marketing analytics solutions. With a seemingly endless list of options, picking the right tool can be tedious. Accordingly, the following post hopes to make this decision-making process easier by comparing Oribi with a similar analytics tool, Wicked Reports.
Which caters best to your web analytics, revenue attribution & reporting needs?

About Oribi

May 2022 Update: Linkedin's recent acquisition of Oribi has triggered major changes. While Oribi is being integrated into LinkedIn’s marketing solution, most (if not all) its features are being discontinued with immediate effect. This includes third-party integrations like Google and Facebook ads as well.

Oribi is an Israeli-based private organization founded in 2015 that develops a marketing analytics platform that provides code-free integration and automated event tracking across your website. They package a variety of CRO features like customer journey funnels and event correlations within a simple, user-friendly platform.

A popular attribute of Oribi is that its interface is easily accessible. It not only showcases your site’s highlights, but also uses algorithms to recommend and group critical interactions which can be customized and filtered. 

About Wicked Reports

Founded in 2015 and based in the United States, Wicked Reports is a marketing attribution platform with a wide assortment of campaign analytics and breakdowns. It employs a wide range of attribution models that can be customized and then filtered for a date range, source, medium, campaign, product, etc. This attributed data can then be presented in the form of ROI reports along with other metrics such as CAC, CPL, recurring sales, and more. It also generates insights into customer lifetime value and cohort analysis, predictive behavior reports, etc. 

Some of its unique features include the ability to include/exclude subscription revenue, distinguish new sales from recurring sales revenue, and new leads from re opt-ins. Not to mention its partnership with Google for an AI-based campaign bidding section known as Wicked Google Conversion Optimiser.

Oribi vs Wicked Reports

Both Oribi and Wicked reports have similar end goals — to monitor marketing performance and optimize conversions. That being said, they are fairly different operationally as some features are more predominant than others on either platform. To highlight these differences, let’s discuss their prevalent use cases and limitations.

Oribi Use cases:

As mentioned earlier, please note that the following features and use cases of Oribi will not be operational as a result of their recent acquisition by Linkedin

Web Analytics

When it comes to Oribi, web analytics is its bread and butter. It starts with codeless event tracking across button clicks, page visits, and form submissions. These events can be easily exported to other integrations. And all of the event metrics like visits and conversions by channel, device, UTM, page, session, funnel, etc can be reported individually per event. 

A feature known as magic events automatically recommends critical events to track, which can also be customized and grouped. If you are interested in learning about what interactions a visitor is more likely to do based on correlated actions, Oribi’s event correlations feature does exactly that 

Funnels

Another feature that Oribi has over Wicker Reports is it’s funnels. Besides being able to break down your conversion rates by a funnel when inspecting your events, Oribi allows you to create and customize your own funnels using any button click, page visit, and form submission. What was special about Oribi is that you could build funnels across different domains and across different web sessions. Once you build a funnel, you can even filter them based on platform, channel, locations and more. 

Customer Journey

Oribi’s visitor’s journey section allows you to peer into any visitor’s entire journey on your website. It displays a detailed breakdown of all interactions by the visitor, the time between actions, channel, platform, OS, etc. If Oribi is tracking more than one domain, it will track visitors across all domains whether it’s in the same web session or not. You can also look for a specific visitor using email integration, and other filters like engagement, channel, actions performed and more.

Marketing Attribution

Perform channel level attribution with the option to filter different events as conversion goals with Oribi’s attribution feature. This facility presents single-touch and multi-touch models alongside channel level touchpoints for your conversion goal. Oribi’s attribution tool is a good way to understand which attribution model works for your website, which you can then weigh using Oribi’s attribution calculator.

Oribi Limitations

Discontinued operations

As of the acquisition of Oribi, their biggest limitation is that they have shut down their services as Oribi permanently. Not only did they stop onboarding customers, but a large portion of their existing customers have switched over to other services. 

Limited metrics

‍Oribi has limited cost/revenue-related metrics at a product level, they only highlight basic metrics such as total sales, average order value, ROI, etc. They miss out on other pivotal metrics like CAC, CPL, LTV, etc. The same can be said even at a campaign level.

Lackluster attribution

‍The attribution feature is only capable of channel level attribution, and can be filtered by a few web events based on clicks and page visits. This is inadequate as attribution becomes actionable only when the whole picture is visible. Only attribution across campaigns, web, CRM, offline touchpoints provides comprehensive insights.

Limited attribution metrics

More specifically, Oribi’s attribution and its inability to assign cost/revenue-related metrics to attribution like ROI and CLTV. Again this has to do with the fact that Oribi does not attribute at a product or campaign level and only focuses on attributing event traffic. Oribi’s attribution calculator allows you to assign a model/crediting system to your web based attribution at a channel level. This information is superficial as you cannot decipher what campaigns drive more revenue per channel.

Miscellaneous limitations with Oribi

• Query data has long load times, and the dashboard fails to load certain reports.
• Limited reporting, can only produce reports as a pdf document and not other formats such as .csv and xlv.
• Cannot perform call tracking, inbound search query, and keyword tracking.
• Cannot track web events specific to a product.
• Oribi’s pricing is not very affordable for small businesses and startups.
• Inadequate technical support, sometimes unresponsive. 

Wicked Reports Use cases

Marketing attribution

Wicked Report’s attribution is its most powerful tool which is used to make ROI reports. Despite being called an ROI report, these reports present way more than just attributed ROI. To explain, let’s understand how the feature works.

Before generating a report, users can pick from a range of attribution models. The selected model serves as the base on which campaigns are credited.

The following models available as of today:

• Customize Last Click Attribution
• Linear ROI
• First Click ROI
• New Lead First Opt-in ROI
• ReEngaged Lead Re Opt-in ROI
• Full Impact ROI
• Last Click ROI
• Attribution Model Customization and Settings
• ReEngaged Lead Attribution Setting

After picking an attribution model, you can apply a wide array of filters including date range, source, medium, campaign, product, etc. From here, every campaign’s ROI will be calculated based on the model. The campaigns will be presented along with metrics such as clicks, leads, sales, ROI, AOV, CPC, EPC, CPL, CPA, etc. You will also be able to examine things like first and last click sales and revenue for multi-touch models.

Customer journey

The only way to view campaign-level customer journey reports on Wicked Reports is to create an ROI report and access customer journey reports for each campaign individually.  For a wider breakdown, the customer journey explorer reverse engineers all channel interactions from total revenue to sales (last click), to new leads and finally first click. Each campaign from the reports will have an option to view the customer journey through which you can map the conversion journey of each campaign — at a source, campaign, keyword-level

Sales velocity and forecasting

The predictive behavior reports combine a boatload of historical CRM data from HubSpot, Klaviyo, etc. It then merges it with sales data from Shopify, ReCharge, etc., to create a sales velocity report. After analyzing all the historical data, it presents a set of graphs and metrics. This illustrates favorable sales days and sales hours along with a forecasted evaluation time based on its calculations.

Cohort reporting

Cohort report on Wicked Reports presents a graph that keeps account of the customer’s ROI and value in preferred intervals over time. This information demonstrates the customer’s profitability over time from its monetary value and ROI. This can be used to adjust the CAC over time. This report also presents other useful information such as LTV and the break-even based on the month’s revenue.

Wicked Reports Limitations

Limited event tracking

‍For its attribution and customer journey features, Wicked Reports track button clicks. Missing out on other events such as page visits, form submissions, session times, etc affects the ability to customize your analysis and effectively attribute your marketing efforts.

Missing funnels

‍Wicked reports cannot construct customer journey funnels. The ability to create, customize and filter funnels allows you to see where you lose your visitors. Customizing your conversion flow is vital to optimizing your conversions. A good reason as to why they don’t have this feature is because of their event tracking, or lack thereof.

Web-level attribution

Despite attribution being one of its strong points, Wicked Reports cannot attribute at a web level. Even though they mostly track button clicks that shouldn’t stop them from allowing users to choose a conversion goal. Their conversion goal is always sales. However, it is an “ROI report”, so it is justified. But that doesn’t alleviate the fact that it can’t be attributed at a web level.

Lacking content analysis

‍Sure, Wicked Reports could technically attribute and even present metrics on content so long as it’s part of a campaign activity. It has no dedicated function that for one, distinguishes its content marketing from its adverts (outside of an organic vs PPC filter). And two, focus on a client’s content strategy and performance.

Miscellaneous Wicked Reports limitations

• The Attribution is not always accurate, values change due to reweighing attribution credits.
• Limited comparative reporting features — cannot compare attribution models.
• There is no in-platform extension for its ad integration to manage ads.
• Outdated and Clunky UI, hard to manage the columns in the reports.
• Takes a lengthy period of time to load reports, anywhere from 12 to 48 hours.

Factors.ai is able to fill in this void. A marketing analytics and attribution solution like factors.ai comes equipped with an extensive list of event tracking capabilities — including button clicks, page view, form submissions, session time, cursor movement, etc. Factors.ai can not only build and customize funnels from the get-go, but can also filter them — at a channel, campaign and keyword level along with a breakdown of all the funnel metrics. Neither Oribi nor Wicked Reports can hold a candle to factors’ attribution facility. Attribute across channels, campaigns, web events, CRM, keywords, etc., making use of several models and custom ones under any conversion goal. Optimize your conversion rate and enhance your content marketing with factors’ content analytics, with access to a multitude of content metrics and dozens of insights.

See for yourself. Book a personal demo with Factors.ai today.

Marketing Analytics, Web Analytics, and Customer Journey Funnels

Now more than ever, marketing analytics, web analytics, and customer journey mapping is at the core of every marketing strategy. That being said, tracking, collecting, cleaning and formatting data is a laborious chore. Most organisations, especially SME firms, have neither the time nor the resources to devote to these steps. What's more? Only after you have all the data in place can you analyse, report and optimize marketing efforts.

This is where organisations use self-serve marketing analytics solutions to collect and analyse data. There's no shortage of tools trying to solve for quality, self-serve analytics. Picking the right one, however, can be tricky. One such web analytics solution, Oribi, was recently acquired by LinkedIn for over $80 million. As a result of the acquisition, former Oribi-users are on the hunt for alternate solutions — one of them being Heap.

Heap

Founded in 2013, Heap is a San Francisco based product analytics platform that provides insights and data visualization to track customer engagement with a company’s site or product. It maps user behaviour and enables users to quickly access and organise data to recognise sources of friction within the user journey.

Oribi

Oribi is an Israeli based web and journey analytics platform founded in 2015. Oribi helps track site interactions and key conversions. It also allows marketers to get action-oriented and data-backed trends and insights. Additionally, Oribi helps users understand visitor journeys with intuitive, user-friendly reporting mechanisms.

Heap Vs Oribi: Analytics and Integrations

Although marketers can (and do) use both Heap and Oribi to access user journey data, Heap is marginally more intuitive when it comes to tracking user journeys on web-based products. Oribi, on the other hand, is better suited for pure web analytics.

Another point: Heap does not support direct integrations with ads platforms like Google ads or Facebook ads. To be fair, Oribi’s integrations with Google and Facebook is also set to be discontinued as a result of the Linkedin acquisition. When it comes to CRM integrations, Heap allows for both Hubspot and Salesforce. Meanwhile, Oribi only users to push data back into HubSpot.

Heap works by placing a snippet of code at the top of the site and tracks user journeys only on your website or your product. Its primary use cases are product adoption, product-led growth and funnel tracking for the digital experience over the website or application. Heap also enables site search tracking and campaign management. Oribi does not.

Oribi’s funnel helps marketers understand what journeys buyers are taking and where they are losing more users so that marketers know what they have to work on to improve. Similarly, it gives insights as to which type of content works best and drives more buyers to convert.

Shameless plug but Factors.ai delivers the best of both worlds. Strong campaign analytics, web analytics, revenue attribution, funnels, button tracking and more — across ads, web, and CRM. Schedule a personalized demo to learn more :)

Heap Vs Oribi: User Interface

Oribi has often been praised for its simple to use UI. Heap, on the other hand, has been found a bit wanting in terms of ease of use. Oribi has consistently ranked higher across factors like UI, ease of set-up, ease of admin, real-time reporting, etc. However, Heap may have the edge in terms other features like retroactive reporting, integrations and custom event tracking. Although Heap is a non-code platform, users with zero experience have often found the tool a bit complex to set up and the learning curve steeper than in the case of Oribi. 

Factors also ranks high (in fact, higher than even Oribi) across ease of use, onboarding, customisable filters and breakdowns for reports. Learn more here! 

Heap Vs Oribi: Multi-step digital journeys & multi-channel digital journeys

Both Heap and Oribi help organise and track customer journey funnels. But the funnels are of different kinds.

Heap has been proven to be best for tracking the funnel in a multi-step digital journey, this means that if the user has to take several steps in their digital journey over the application/product or website to get to the end goal or to convert, Heap gives insights as to what steps the user took, in what sequence, when did they complete the goal, where they faced frictions, what step took more time, etc. Their effort analysis features allow you to see what parts of the site give more trouble to the user and why. 

On the other hand, Oribi is preferable for marketers to track the funnel in a multi-channel buyer journey. In other words, if you want to see where your potential buyers are coming from, and what actions they’ve taken before they’ve come to the website, a tool that focuses on tracking multi-channel journeys is more useful. Particularly in the case of B2B user journeys, where there are multiple decision-makers, each of which interacts with your product/service on various marketing channels over a longer sales cycle, multi-channel attribution tracking and efficiency measurement of overall campaigns becomes more important for the marketing team.

Pros and Cons of Oribi and Heap

Heap Advantages

1. Real-time reports: Heap’s auto-tracking and data governance tools ensure that every single event and every single user is tracked and these data points fit into a data structure from the moment that they are collected. This ensures that the reports are always real-time and the data structure is able to adapt even when events change — without any code or engineering support.
2. Allows for retroactive analysis: Since users can retroactively define events and conversions, the data structures and dataset organisations evolve to fit deliverables when they change.

Heap Disadvantages

1. High cost of data storage: Because every single user and every single event is automatically tracked on a real-time basis, this leads to a large quantity of data that has to be stored. 
2. Website analytics focussed: Although Heap supports several integrations, it is more focused on user’s interactions and journeys on the website/product. It also misses ad platform integrations due to the same reason. B2B marketers cannot map out entire customer journeys which in turn, can make it harder to derive insights into overall sales patterns. 
3. Difficult to use: Its UI is a little complex as compared to Oribi. The learning curve is steeper. 

Oribi Advantages

1. User interface: The interface and dashboard are intuitive and easy to use for anyone within the organisation. 
2. Automated data orchestration: Oribi’s ability to automatically send data back into platforms like Hubspot and Google Analytics helps with data orchestration and breaking down of siloes across different storage locations.

Oribi Disadvantages

1. Oribi’s CRM integration allows it to send data automatically to Hubspot but it cannot take data from the platform to integrate CRM data for attribution on the user’s larger customer journey on its own platform. 
2. Oribi’s reporting capabilities have been found lacking as it does not allow for custom filters, breakdowns and formats for data visualisation. The reporting section only allows for pdf reports which can limit how much you can include/exclude.

In closing,

The biggest difference between the two is that Heap is primarily a product analytics tool and Oribi, a web analytics tool. However, because most B2B SaaS products are web-based, the functions of product and web analytics bleed into each other. So Heap is also used for web analytics and vice-versa. At the end of the day, there are several analytics tools that help marketers automate grunt work like data collection, organisation and formatting. They come with different features that help solve various use cases in the day-to-day working of the team. To choose which tool is best for you and your organisation, identify what you struggle with and what tools provide best for such use cases. 

We suggest you check out Factors to get the most out of your data!