Ranga Kaliyur

The following post is the second part of our “Attribution is Broken” series.

Here’s a link to the introductory post if you’re interested.

I recently came across an Instagram ad for a shiny new pair of noise-cancelling headphones. Being the mindless sheep I am, I decided that I needed a pair. So after some light research involving a few customer reviews and price comparisons, I went ahead and bought them. From start to finish, the purchase process took me about an hour or so. Admittedly, the headphones set me back a little but who cares? I can always return them if I’m not happy right? This was a short and sweet journey that’s easily digestible by most multi-touch attribution tools. And yet, this journey takes quite the turn when marketers want to reach out to businesses instead. 

B2B purchase decisions are tricky affairs. They involve complex high-value contracts, lengthy sales cycles that stretch over several months, and limited scope for backtracking once confirmed. As a result, all B2B purchases — especially those made in technology — are critical decisions. So, to mitigate the risk of making poor purchases, organisations include multiple stakeholders across multiple departments over multiple levels of seniority in their decision-making process. As an unfortunate consequence, however, this involvement of heterogeneous stakeholders tremendously complicates the account’s journey from awareness to purchase. 

Here’s a simple example of a complex B2B sales cycle:

HubForce, a promising CRM start-up takes out a couple of ads on Linkedin and Facebook.   They also publish content in the form of blogs and host interactive webinars on a regular basis. Additionally, HubForce’s SDR team requests demo meetings from CSOs, Demand Gen VPs, and Project Managers on a daily basis through outbound emails.

Ali, who is project head at Drifter (a leading chatbot service provider), receives one such mail. Ali happens to be in the market for a CRM tool and schedules a demo with HubForce. HubForce’s sales head, Vinay, walks Ali through the several technical features they have to offer. This includes HubForce’s ability to integrate with Drifter’s current tech stack and a cutting-edge AI tool that automates a lot of Ali’s grunt work. Ali is impressed and wants to onboard Hubforce. However, he needs to run the purchase decision by his CEO, Anaiya, before making it official.

Upon hearing Ali’s rave reviews, Anaiya is curious to learn a little more about HubForce.       She reads a couple of their blog posts and digs up a few reviews written by existing customers. Being a fastidious CEO, Anaiya also schedules a follow-up meeting with Vinay. This time around, Vinay demonstrates what HubForce can bring to Drifter’s revenue and sales pipeline. Rather than zone in on technical details, Vinay focuses on HubForce’s big-picture gains instead.  Anaiya likes what she sees but wants to discuss their budget constraints with her finance chief, Albert, before signing on the dotted line.

During their weekly catch-up, Anaiya fills Albert in on the HubForce deal — specifically the pricing details. Albert isn’t thrilled. He’s of the opinion that Drifter would be overpaying for what’s essentially a roided-out excel. Upon hearing this, Anaiya decides to put the deal on hold until next quarter. During this time, Albert is frequently targeted by HubForce ads on Linkedin. He even attends one of Hubforce’s webinars on their cutting-edge, AI-powered CRM technology. Eventually, Albert is convinced of the value that the CRM platform could bring to Drifter.

As the next quarter rolls around, Ali, Anaiya, and Albert discuss the deal one last time. They weigh the pros and cons and arrive at a unanimous decision to purchase a HubForce subscription. Congratulations you guys!

Clearly, the previous purchasing process was far more complex than the case of the headphones. A nuanced web of back and forth interactions had to take place before the deal could be closed. As a marketer looking to replicate this process in a scalable manner, multi-touch attribution is your go-to tool. Attribution modelling empowers marketers to unravel their intricate customer journeys, and understand the performance of nearly every marketing activity. Attribution reveals, to a large extent, what campaigns are working, and what campaigns aren’t. In turn, marketers can make data-driven resource allocations across their marketing activities. All that being said, attribution isn’t without its challenges when it comes to dealing with multiple stakeholders.

Across the length of the previous example, HubForce depended on a variety of content, strategies, and channels to get their deal across the line. They had to sell different aspects of their products to different types of audiences. Project managers may care about practical details like integration, accessibility, and time-saving. CEOs may be interested in high-level gains like ROI, pipeline, and revenue. Finance heads want to know that they’re getting the best possible price. On top of all this, each position is filled by individuals with their own motivations and preferences. The one-on-one demo clearly worked for Ali, but Anaiya chose to perform some background research as well. Albert, on the other hand, was convinced after a couple of targeted ads and a relevant webinar. All these variables contribute to the challenges of B2B attribution:

The B2B Buyer Dichotomy

B2B marketers engage with individual contacts through personalised emails, targeted ads, etc. However, the purchase decision ultimately involves a buying committee. In the example discussed above, there are three stakeholder groups that make up the buying committee- the core buying group (Ali and his project team), the group that focuses on negotiating terms (Albert and his finance team), and finally, the group which exercises the final approval (Anaiya, the CEO).

The core buying group initiates the process by identifying the need for the product, ideates on the potential solutions, and looks for options. The group that negotiates the terms will focus more on protecting the company’s interests. This involves the members from teams like legal and finance. Lastly, the final approval stakeholder group has the final say or authority. The focus of this group is to look at the company’s larger aims and strategy implementations. 

The marketer has to align these diverse internal stakeholders during the sales journey.

Different Strokes for Different Folks

Now that the different internal stakeholders within the buying committee have different core focuses, the marketer needs to adjust their approach to each group depending on what they care about. For instance, in our example, finance cares more about the pricing, while the CEO cares about the revenue and ROI, and finally, the marketing team would care about metrics like conversions, pipeline, etc.

In addition to this, the sales cycle is often complicated and non-linear. Complex B2B purchases such as enterprise software, have a lot more information for the buying committee to consider. This process becomes more drawn out with the complexity of the solution and the presence of alternatives. The multiple stakeholders in an account who have different preferences and objectives, may revisit the various stages of the buying process non-sequentially and sometimes, simultaneously. The stakeholder behavior can also be loopy where they may switch between being interested to not interested to being interested again, as we saw in our example.

Each stakeholder group keeps referring to each other in non-linear learning loops before they come to the final decision of moving forward with the purchase or not.

Invisible Touchpoints

The touchpoints in our sales cycle are of different types. While digital ads, reviews, page views are visible, there may be some that are invisible. Attribution models trying to map stakeholders might be unable to account for these touchpoints. For instance, in our HubForce example,  the finance head, who was not entirely on board with the CRM purchase, attends a webinar which finally leads to the deal being won. Data issues can arise if your CRM and marketing automation data are not flowing properly. In this case, if the impact of the webinar has not been stitched in the sales journey.

Today, most B2B marketers employ a single attribution model across a fixed timeline to derive insights from their campaign data. Sure, this approach is easy, quick, and uncomplicated. But it is also dangerously inaccurate. The issues brought on by the involvement of several stakeholders (Heterogeneous preferences and objectives, long sales cycles, loopy (back and forth) behavior of interest, and a diverse range of touchpoints) render simple attribution modelling ineffective. Instead, marketers should aim to treat each group of users independently and attempt to learn what works best for each one of them. This involves parsing out each type of customer and individually employing the appropriate model. This approach allows you to ask nuanced questions and derive genuinely actionable insights. Of course, this is a far more advanced process than an all-encompassing approach — but it’s infinitely more accurate as well. 

So what’s the solution for implementing incredibly advanced attribution models? 

Well, an incredibly advanced attribution platform of course! 

Learn more about Factors.AI cutting-edge attribution here.

Podcasts are bigger than ever. The number of series worldwide have shot up from an already sizeable 500,000 in 2018 to a whopping 2 million in 2021. Unsurprisingly, podcast consumption has also been rising steadily over the past 15 years. In fact, nearly 60% of all American adults report that they’ve listened to at least one episode this year.

And Videos? They're bigger still. A third of all online sessions are spent consuming videos — everything from sleep talking cats to educational/explainer videos. To sit down and watch every single one published over the past month alone would require approximately 5 million years. And the best part? Nearly all of this is available on the internet for free. As a result, audio/visual content is more accessible, and hence, more popular than ever before.

The opportunistic folk that we are, B2B marketers have taken little time to capitalize on this wave. I can’t remember the last time I scrolled through my Linkedin feed without stumbling across a post for a friend’s friend’s colleague’s boss’s brand new B2B SaaS RevOps podcast. In fact, upwards of 85% of businesses today produce audio/video content as part of their marketing efforts. They are by far the fastest growing marketing channels out there.

And why not? 

Just like any other marketing channel, podcasts and videos can be effective mediums to communicate a specific message to a specific set of people. They are relatively easy to ideate, produce, and distribute. They require little investment from either the supplier or the consumer. And they’re far more palatable than a 20-page white paper. 

Yet, while audio/video content can be valuable assets, marketers face one glaring issue when it comes to identifying and measuring their ROI in terms of conversions — trackability. As is the case with any marketing activity, marketers are keen to understand how their content is performing. However, since anyone can listen to a podcast, or watch a YouTube video anonymously through any device, it becomes nearly impossible to accurately track how your content is contributing to pipeline and revenue. 

How then must a marketer go about gauging their content's performance? 

While there is no perfect solution to this quandary yet, here are a few tips to indirectly optimize your attribution process:

1. Unique URLs

Create a unique URL for every podcast/video you produce. Drive all your marketing efforts (social media posts, emails, etc) towards that URL. And use that URL as a proxy to track detailed information on who’s landing on your page. Once this data is consolidated, it can be stitched onto the remainder of your customer journey (ads, website, CRM, etc) using Factors.AI. Ultimately, this will indirectly provide insights into your content's pipeline contribution.

2. Distinct promo codes

Along similar lines as the previous point, it might be worth employing distinct promo codes for each piece of content you release. The logic behind this is that when a prospect enters a specific code, it provides an immediate signal as to where they’re coming from. This information can then be accounted for in your CRM for further analyses. That being said, a few issues may occur if listeners/viewers refer the promo codes to their networks. As there’s no automated method to verify the same, one may run the risk of corrupting their datasets and insights. 

3. Don’t forget your Guests

Speaking of recording contact data into your CRM, always ensure you do the same with your guests as well. More often than not, guests are invited to marketing podcasts for two of two reasons — one; they’re experienced professionals with vast knowledge on the topic of discussion. And two; they themselves fit the Ideal Client Profile (ICP) that the host company is going after. Inviting a guest onto a podcast is often simply a wind-about route to securing a demo call. With this in mind, it’s important to account for your guests. This way, if they do eventually close a deal with you, the podcast is present as a definite touchpoint. 

4. Just ask!

Audio/Visual content attribution is a real challenge. There are only so many behind-the-scenes steps you can take to optimize for an accurate customer journey. That being said, one sure shot approach to tackling this evasive phenomenon is to simply  ask your customer about their journey to purchase. Maybe a friend told them about it, maybe they read a positive review on ProductHunt, or maybe, just maybe; they loved that one demo video you released last week! Either way, it doesn’t hurt to ask. 
And there we have it!

Though they’re far from perfect, we’ve covered a few simple tricks to track customers who become customers as a result of a degree of influence by your AV content. Listen/View counts and geographical metrics are decent metrics to gauge content performance. But drilling down into who is sliding down the funnel as a result of your content is pivotal. Using unique URLs and Promo codes, and making a habit of accounting for your guests are great ways to grasp a high-level understanding of your content's contribution to revenue and pipeline. And if it comes down to it, just asking your customer about their journey will also be fruitful .

Human beings are social animals. Over thousands of years, we’ve developed gestures, languages, and tools to express ourselves to those around us. Our exceptional ability for communication has empowered us to exchange ideas like no other species on the planet. Given that this dialogue is at the heart of the human experience, it’s of little surprise that Conversational ABM is becoming an increasingly effective engagement technique for the modern-day marketer.

TL;DR:

• Conversational ABM is a marketing strategy that uses chatbots or live chats to actively engage with target accounts.
• It is crucial to identify and segment your prospects since the demography of each prospect could vary.
• Set proper boundaries when assigning SDRs and ensure that the visitors are routed to appropriate SDRs. 
• Ensure you’re running personalized ads to each prospect and provide relevant and consistent messaging throughout. 
• One of the best platforms to converse with your prospects is LinkedIn.
• Be ready for your prospect at any time by using AI-powered chatbots.

What is conversational ABM?

Conversational ABM is a marketing strategy that uses chatbots or live chat to engage actively with target accounts. 

With real-time conversations, businesses can build strong relationships with their target audience and address specific needs. In addition, it creates a more human connection with prospects, leading to a higher likelihood of closing a deal. 

And because 90% of prospects identify live messaging as their most favored channel of business communication, conversational ABM is a strategy worth considering.  

How to implement a Conversational ABM strategy?

1. Identify your target accounts

As is the case with any ABM strategy, your first step should be to align marketing and sales through a collaborative identification of accounts. 

The target list is usually determined by a few specific firmographic characteristics such as industry, revenue, and geography. Once generated, this list will dictate the tone and language of your messaging, content, and campaigns. So getting it right is pretty important. 

2. Identifying and segmenting prospects

Once you’ve created a fresh list of target accounts, the next step is to identify individual users at these target accounts to reach out to within this list. Maybe you want to target CXOs, or maybe managers, or maybe engineers, or maybe a combination of a variety of such roles.

Regardless, the optimal approach for each demographic will undoubtedly vary. Hence, it would make sense to segment this list of prospects further by customer life cycle, sales stage, pain points, and, most importantly, intent. Then the person in charge allocates this segmented list among Sales Development Representatives, who can work out distinct marketing strategies for their targets.

3. Building boundaries

In an ABM approach, it is important to assign individual Sales Development Representatives to build a strong relationship with each prospect. 

When assigning SDRs, always keep in mind to set strict ownership boundaries. It helps route the visitors to appropriate SDRs and eliminate any engagement overlaps. 

4. Personalizing ads

Okay, now you know whom you’re contacting and why. Now it’s time to think about the approach for each prospect. This stage involves an intricate balancing act between personalization and scale. 

Of course, every individual in every role across every company you’re targeting has their own unique preferences — but personalizing ads at that level isn’t feasible. Instead, customizing ads on a higher level — say, by role or industry, is the way to go. This entails running campaigns based on prospect-specific pain points, and value adds. 

A CMO may care about marketing’s influence on revenue, while a marketing manager may be interested in improving workflow and automation. Your campaigns should resonate appropriately with all such use cases.

5. Sentry Surveillance

Your target list is ready, and your personalized ads are running. Now, the second a prospect from your list is on your website, your marketing + sales teams need to be conversation-ready. 

The first step here is to make sure everyone has access to all the information they’ll need. It means all your CRM data, marketing automation data, and intent data should be consolidated, organized, and easily accessible. Once equipped with all relevant information about the visitor and their company, your SDR team is all set to engage with the prospect.

6. Complete consistency

Personalization is the most important aspect of conversational ABM when a prospect is currently on your website. 

Assuming your prospects love your ads and visit your website, they should be landing on a homepage that’s relevant to them. Any decent content management system (CMS) will be able to identify a contact when they land on your homepage and cater to the web flow in a manner that ensures a personalized experience. 

7. Chit-Chat

A relevant landing page will definitely help direct prospects toward your product. But a lot of the time, this won’t be sufficient. 

A target will stay on your website only for a few precious minutes, and it’s important to make the most of it. Sure, you could wait until they make their way to the demo form and submit their details — but Conversational ABM encourages marketers and SDRs to proactively reach out through a relevant live-chat message. 

References to the contact’s role, the company’s signals, or a prominent pain point are all great ways to get the conversation going. This is the meat and potatoes of the Conversational ABM process. SDRs utilize target data to provide a genuine, relevant, and personal dialogue with their prospects to confirm a demo and push accounts through the funnel

8. Conversational ABM - Around the clock

Conversational ABM involves interacting and connecting with prospects around the clock. While thorough research and proactive interactions are valuable tactics, you may want to employ AI-powered bots to render the process air-tight. So when you do happen to get that one inbound demo at 4 in the morning, you can trust that your chatbots will be up to schedule that demo for you. 

Oh, and another thing — conversational ABM doesn’t top conversations on your website. Linkedin is your friend when it comes to interacting with your target’s content posts. Feel free to leave likes, comments, and, if appropriate, connection requests with prospects. 

Conclusion

And there we have it. When executed well, conversational ABM can be a valuable strategy to bolster your marketing efforts and improve conversions. Though it’s definitely a lot more effort than traditional marketing techniques, conversational ABM pays its dividends in the long run. Prospects form stronger associations with the product and are almost certainly more likely to convert from a distant target to a tight-knit customer.

Factors.ai enables easy integration with CRM platforms like HubSpot and Salesforce. This  can help you generate a more effective ABM campaign. Signup for free or book a demo to start your Conversational ABM campaign today. 

Strike Three, You're Out!

Austrian data regulator, Datenschutzbehörde, recently found Google Analytics to be in violation of EU’s General Data Protection Regulation (GDPR) laws. It was revealed that data collected through GA from NetDoktor, a European medical news website, maintained inadequate protection against American intelligence agencies. Following the infamous Privacy Shield ruling in 2020, and a breach in European Parliament's Covid-19 Website in 2021, this is the third instance of GA operating an illegal mechanism to transfer data across borders in recent years. 

“This transfer was found to be unlawful because there was no adequate level of protection for the personal data transferred. Website operators cannot use Google Analytics while simultaneously being in line with GDPR”
— Matthias Schmidli, Deputy Head, Austrian Data Regulator

What’s especially worrying is that there was nothing uncommon about the way NetDoktor had been using Google Analytics. Like millions of other GA users around the world, NetDokter places third-party cookies on visitors so as to be able to capture user behaviour. The problem is inherently with Google Analytics, as all this data then travel’s back unchecked to the tech giant’s servers in the US.

Europe is increasingly agitated with the manner in which this exported data is being transported and stored. US surveillance laws* protect foreign data far less rigorously than they do domestic data. The uncomfortable implication of this is that, in theory, US surveillance agencies have the authority to harvest massive amounts of personal data sourced from big tech companies like Google, Facebook, and Microsoft. 

“What they do right now would be in violation of the fourth amendment if it’s for US citizens. Just because people are foreigners it’s not a violation of the US constitution”
— Max Schrems, Hon. Chair, NOYB

*Refer Section 702, Foreign Intelligence Surveillance Act & Executive Order 12333

What’s Next for Google Analytics in Europe?

After the episode in Austria, 30 other European countries are currently investigating the prevalence and extent of Google Analytics compliance violations.  While any firm decision is yet to be made, the law is explicit in its stance. At least as it stands, it is impossible to conform to GDPR while actively using Google Analytics. The Dutch (Autoriteit Persoonsgegevens) and German Data Protection Authorities are strongly considering banning Google Analytics in the form that it currently exists. It seems only a matter of time before the rest of Europe follows suit. 

What’s Next for Your European, Google-Analytics Running Website?

If there’s one thing to learn from NetDoktor’s complacency, it’s this — don’t be complacent like NetDoktor. Google Analytics is illegal in Europe. Google Analytics is not GDPR compliant. Ignoring privacy rules and regulations may result in expensive fines and damaged brand reputations. If your website is Austria-based — or even serves Austrian citizens — you should ditch Google Analytics immediately. For other EU-based websites, it is highly encouraged to replace Google Analytics with a 100% GDPR compliant tool before local authorities inevitably tighten enforcement.

"Instead of actually adapting services to be GDPR compliant, US companies have tried to simply add some text to their privacy policies and ignore the Court of Justice. Many EU companies have followed the lead instead of switching to legal options."
— Max Schrems, Hon. Chair, NOYB

Factors.ai is the #1 privacy-first Google Analytics alternative for your consideration. We provide end-to-end marketing analytics and revenue attribution using absolutely no third-party cookies. We’re also 100% GDPR, CCPA, and PECR compliant. Additionally, we recently secured SOC2 compliance — satisfying the Trust Services Criteria based on Security, Availability, Processing integrity, Confidentiality, and Privacy. Book a Demo with us to learn more about Factors.ai.

Official Oribi Update:

As of May 2022, Oribi has officially discontinued its services and contracts following its acquisition by Linkedin. As a result, several (if not all) of the following Oribi features are no longer operational. This includes integrations across Google and Facebook, web analytics, channel analytics, attribution, and more. Over the past few weeks, dozens of former Oribi users have migrated to Factors. Rest assured, they've been delighted with the experience. Book a personalized demo to learn more.

‍Oribi is great…but!

The B2B marketing analytics and revenue attribution space is booming.
As organizations allocate increasing budgets towards their marketing efforts; optimizing ROI and determining revenue impact is becoming a growing priority. Accordingly, there’s an explosion in demand for tools that help marketers understand their data. There’s no better testament to this claim than Linkedin’s recent acquisition of Oribi for over $80 million.

Oribi is fantastic for B2B website analytics. It’s simple, reliable, and great at what it does. Users rave about Oribi’s intuitive UI, web-based insights, and valuable CRO features. That being said, Oribi has certain fundamental limitations that Factors solves for. The following post compares the two platforms to demonstrate why Factors makes the better fit for B2B marketers.

It starts with the data…

Robust marketing analytics starts with robust marketing data. Data from ad campaigns, web sessions, and CRM events contribute to pin-point analysis and actionable insights. Accordingly, the strength of integration between your data sources and your analytics platform is a major factor to consider. Let’s explore how Oribi and Factors compare when it comes to data integrations. 

The table above shows that both Oribi and Factors share a few common integrations including Google Ads, Facebook ads, and Hubspot CRM. What must be highlighted, however, is that the functionality of integration varies significantly between both platforms. For example, Oribi can push web data back from its platform to HubSpot and Factors cannot. Similarly, Factors can pull HubSpot and Salesforce data for customer journey analysis, while Oribi cannot.

Oribi is for you if…

Data orchestration is your priority. If pushing website data like button clicks and form submissions into HubSpot or Google Analytics is what you’re looking for, Oribi is definitely the better option. As it stands, Factors cannot automatically send data back into other platforms like Oribi can.

Additionally, Oribi provides three valuable integrations that Factors does not — ActiveCampaign, Mailchimp, and Klaviyo. As a result, use-cases that Factors misses out on includes: 

1️⃣  Personalizing CX for ActiveCampaign contacts based on web behavior

2️⃣  Triggering personalized emails based on website behavior through MailChimp

3️⃣  Using Klaviyo to build targeted customer segments and campaigns

Factors is for you if…

Making sense of your marketing data is a priority. Factors delivers a far superior marketing analytics and revenue attribution experience as compared to Oribi. This ultimately lends to refined data-driven marketing strategies, campaigns, and more.

🔴  Oribi only pulls Total Spend metrics from ad platforms like Google and Facebook. What’s more? These reports are limited to channel level data. Factors, on the other hand, consolidates all metrics including CPC, CTR, ROI, impressions and more — at a channel, campaign, ad group, and keyword level.

🔴  Oribi’s integration with HubSpot is limited to pushing web data back into the CRM. It is impossible to report CRM data or attribute CRM milestones using Oribi. Factors integrates with HubSpot and SalesForce to connect campaign and web data with contact data, offline events, and revenue metrics from your CRM. This empowers end-to-end analysis and attribution across the length of your customer journey. More on this later.

🟢  Factors integrates with Clearbit Reveal to deliver powerful de-anonymized website data. This means that you can identify the accounts and leads visiting your website without requiring them to fill in a contact form. This is an integration feature that Oribi does not offer.

Why Marketers Prefer Factors Over Oribi

Reporting

Before optimizing your marketing strategy, you need a clean, comprehensive overview of your marketing data. Here’s why Factors has the edge over Oribi when it comes to reporting data:

1. End-to-end marketing reports 

Oribi specializes exclusively in website analytics. This is both a strength and a shortcoming for the platform. Oribi fails to report on campaign performance and metrics across Google Ads, Facebook ads, and Linkedin ads. Additionally, it cannot report back with CRM data like lead stage, cost per lead, and revenue. Neither can it report on offline events like webinar attendance, sales calls, and non-web content. Failing to report on this vast array of information consequently affects any further analysis across funnels and multi-touch attribution. More on this later.

Factors delivers end-to-end reports across all your ad campaign metrics, website activity, and CRM data (including offline events). B2B Marketers can access all the data they would ever need under one roof with normalized, shareable reports. Consolidating all this data is in and of itself a major advantage that Factors has over Oribi. It eliminates data silos and ensures alignment across marketing, sales, and customer success. 

2. Limitless filters and breakdowns 

Generating a marketing report is one thing, but being able to slice and dice your reports is what makes reporting with Factors especially valuable. Factors provides unmatched customization across ads, web, and CRM reporting. Marketers effortlessly filter and breakdown reports by several dozen industry-standard properties and metrics. What’s more? Factors enables 100% custom properties, dimensions, and group-by options so your team always generates tailored insights.

Oribi is notoriously inflexible when it comes to reporting. Unlike Factors, there’s no room for custom filters or breakdowns. This implies that marketers receive a finite and often inadequate overview of the data they’re working with. 

3. Flexible visualization and custom dashboarding

The concept of dashboarding simply does not exist with Oribi. As a result, grouping and visualizing reports can be a cumbersome process. On Factors, all reports are housed in customizable dashboards. For example, all your content reports like “blog page visits”, “scroll-depth percent”, and “time-spent on page” can be stored under one dashboard, with your campaign reports stored under another. These dashboards are automatically updated with the latest data across all your marketing efforts. 

Another major benefit with Factors is its beautiful visualization mechanics. Line charts, spark charts, funnels, stacked graphs — we do it all! Marketers always have the option to choose between visual representation of their data that is best suited to their needs.

Marketing Attribution

Right off the bat, it should be mentioned that Oribi’s attribution engine is limited to website event attribution. This means that users can track how a visitor travels from one web page to another before hitting a conversion goal like a form fill or button click. To put it mildly, web-exclusive attribution is of hardly any use to B2B marketers. Lengthy sales cycles, several stakeholders, and countless non-web touchpoints render the B2B buyer’s journey convoluted and non-linear. It is essential to attribute each and every marketing touch point along the way — not just the ones that occur on your website. Here are a few major reasons why Oribi’s attribution doesn't hold up with Factors:

⭕️  Oribi’s limited CRM integration inhibits end-to-end attribution from initial touch point to revenue data (MQL, SQL, contract value, cost per conversion, etc)

⭕️  Oribi provides only channel level attribution (no campaign, keywords, etc)

⭕️  Oribi does not provide breakdowns by campaigns, ad groups, keywords 

⭕️  Oribi doesn't attribute the full suite of ad metrics including CPL & ROI.

⭕️  Oribi does not attribute offline touchpoints (sales meetings, ebook downloads, webinar attendance, etc)

All in all, Oribi’s attribution is a superficial service. Conversely, multi-touch attribution is one field that Factors perform exceedingly well in. The platform provides robust attribution at each relevant level. It delivers a vast range of models, filters, dimensions, breakdowns across all the metrics you care about — from ad campaigns to offline events. With Factors you can:

✅  Attribute marketing interactions across ads, website, and CRM (not just web!)

✅  Attribute offline touchpoints with CRM integration 

✅  Perform revenue attribution at an account level 

✅  Compare multiple multi-touch attribution models against each other

✅  Customize attribution reports with dimensions and breakdowns by channels, campaign, adgroup, and keywords

Content Analytics

How are your blogs, podcasts, case-studies, white-papers, etc. driving pipeline and revenue? Several marketers actively use Factors to generate content reports and gauge the performance of their web and offline content. Content analytics with Factors goes beyond page-views, scroll percent, and time-spent on page. The platform actively connects the dots between content, leads, and revenue to provide a holistic view of what content is converting prospects better than others. 

Oribi delivers similar content reports but its analysis is restricted to website/on-page content. For example, while Oribi can measure the performance of a particular blog on your website, it will not be able to track offline content touch-points like ebooks downloaded through paid ads or email content engagement like clicks and replies Ultimately, this type of content analysis will always remain incomplete.

Customer Journey Analytics 

Understanding and optimizing the customer journey is a core use-case with Factors. Our patented AI-algorithms automates most of the analytical heavy lifting to deliver immediately actionable reports. These insights are based on customer behavior across campaigns, website, and CRM. Here are two popular features used by marketers today:

1. End-to-end Journey Analysis with “Funnels”

Funnels provide marketers with a high-level overview of every step of the sales cycle from first interaction to demo to MQL to SQL to deal won (and anything else in between). As previously mentioned, Factors is far, far more customizable than Oribi across the board and Funnel analytics is no exception to this. Oribi only shows a select few funnel configurations, none of which include analysis at a campaign, adgroup, or keyword level. Factors offers several dozen filters, breakdowns, and metrics. What’s more is that Factors allows users to generate and analyze reports based on custom dimensions and properties. This is not possible on Oribi. 

2. Automated Insights with “Explain”

Both Oribi and Factors provide automated marketing insights. However, a key difference is that the concept of conversion is limited to web events on Oribi. Unlike Factors, which enables marketers to configure custom conversion goals, Oribi only considers website activity and button clicks when generating its insights. This is a 2-fold issue:

1. On average, 5-10% of button clicks are inaccurate (For example, if a visitor accidentally clicks on a “submit now” button without actually filling in the mandatory fields will still be counted as a button click. This, in turn, will produce incorrect insights based on false-data. Factors solves for this by stitching web behavior with CRM records. This way, a form fill is verified by cross validating the submission with your CRM contacts.

2. Since Oribi only captures web events (and ignores CRM data), its insights do not accommodate the entire user-journey. Consequently, conclusions derived from Oribi’s insights could very well be flawed. Here’s a likely scenario of this:

Let’s say you’re running a Display campaign and a Search campaign. With Oribi, you’ll only have access to reports uptil “cost per sign up”. In this case, the display ad seems to be performing far better than the search ad. However, when you unlock the full picture (as you can with Factors), MQL conversions are far more cost-effective with Search ads. Hence, actioning your strategy based on Oribi’s conclusion could result in suboptimal (or even worse!) marketing results. 

Conversion Rate Optimization (CRO)‍

How are your core pages like “features”, “pricing”, and “resources” driving demo form submissions? Where are website visitors spending the most time before contacting your sales team? How is button placement affecting conversion rate? Several marketers rely on Factors to answer these questions about conversion rate optimization. 

It should be mentioned that CRO is Oribi’s forte. If CRO is your sole use-case, Oribi would be the recommended alternative. This is especially true if your business is more e-commerce, and less B2B. With that said, however, it should also be mentioned that Factors stacks up to Oribi across all its CRO functions. The difference between the two platforms is in user experience. Since Oribi’s analysis is relatively surface level, CRO reports are far more accessible and facile to new users. Factors, on the other hand, provide in-depth analysis and hence, isn’t as simplistic. Don’t get it twisted — both platforms are self-serve and require no-code or technical know-how whatsoever. But Factor’s flexibility implies a marginally steeper learning curve as compared to Oribi. 

The Best Time To Switch To Factors

Congratulations are in order for Linkedin's successful acquisition of Oribi. It's a big deal. As a results, however, Oribi's operations are likely to face a turbulent near-future. In fact, at the moment, Oribi is not onboarding new customers. What's more? As promising as this acquisition is, the product road map for Oribi is all but certain. This, coupled with limited customer success and onboarding support does not bode well for the platform. As the previous sections highlights, Factors is objectively the better marketing analytics and attribution platform for B2B marketers. And there's no better time than now to take it out for a spin yourself. Get started for free here or schedule a personalized demo to check out our work!

‍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!