Ranga Kaliyur

As digital marketing takes on new complexities, it’s essential for your marketing plan to incorporate content analytics. This will help you have a more detailed understanding of how customers interact with your company. You’ll be able to make more informed, data-driven decisions to effectively reach and convert your target audience.

What is content analytics?

Content analytics, or content intelligence, is a set of technologies that analyzes digital content in order for you to understand which content is performing well with your target audience. This enables you to create the most effective digital content possible to drive more conversions.

How does content analytics work?

B2B companies often offer highly specialized solutions. Accordingly, businesses must target their niche audiences with dedicated marketing initiatives and content that address relevant paint-points and use-cases.

You can generally figure out which content works best for your clients by analyzing certain metrics for the unstructured content your business has put out. Analytics and attribution tools like Factors.ai help marketing teams with granular insights into content performance and bottom line impact.

It’s important to remember that content analytics and attribution isn’t a linear process. We got in touch with B2B content industry leaders to ask how many metrics they use to measure content performance. Here’s what they had to say:

We also asked them which metrics they think are the most important in measuring the effectiveness of content. Here’s what they had to say:

• Clickthrough rate (CTR): Sophia Madhavan at GrowthMakerz and Vitaliy at Videowise include the CTR in the list of metrics they use to evaluate how well their content is doing. The CTR allows you to see how many times visitors to a certain page organically search for your content or click on your ad as a ratio to the total number of visitors to that page.
• Impressions: Impressions give you insight into the level of engagement your content is generating. This content could be a web page, advertisement, or blog post, for instance. Madhiruma Halder at Recruit CRM lists impressions among the metrics they use to understand how their social media campaigns and search engine marketing are performing.
• Marketing qualified lead (MQL): Not all leads are created equal. A lead that takes any high intent actions like scheduling a demo or signing up for a trial is far more likely to convert than others. Karishma Chopra at Hiver believes that the effectiveness of content should be measured in terms of its influence in driving MQLs.
• Time on page: The time a prospect spends on a particular page is indicative of their interest in the solution you’re offering. Praveen Das at Factors then uses these insights to create marketing campaigns informed by the content their prospects and clients are interested in.
• Scroll depth: Scroll depth is a measure of how far your website visitors scroll down a certain page. As a general rule of thumb, if most of your website visitors are scrolling at least halfway down the page, it indicates that your content has substantial value.
• Unique users: Chelsea Downing-West at The Martec finds unique users a crucial metric. The number of unique users may be challenging to calculate. Effective visitor identification allows you to see how many unique visitors your website receives by counting each visitor only once, no matter how often they visit the website.
• Bounce rate: The bounce rate of your website indicates the ratio of visitors who access your website and leave instead of clicking on and going through other webpages.
• Engaged Accounts: Understanding which specific accounts are consuming the content is another intuitive way for content marketers to analyze its effectiveness. Visitor Identification softwares like Factors can help marketers identify the account and its properties (employee range, industry) even if the user does not fill up a form. This helps Content Marketers plan content efforts tailored to specific industries or scale of employees.

Why is content analytics important?

Your website content is the first thing that prospects see when they’re evaluating your company. It creates a lasting impression about your services. Content analytics helps you understand the types of content that perform well among your target audience, which in turn is crucial to designing a successful customer experience.

Moreover, marketing teams spend a substantial amount of time and budget to create content that prospects find valuable. A few of the experts we surveyed responded that they hire in-house teams for content creation and distribution. This indicates how valuable creating effective marketing content is to increasing overall revenue; B2B companies are willing to invest in salaries, 401(k)s, and insurance to generate engaging content. Respondents stated that they spent anywhere between $1000 and $10,000 a month towards content creation and distribution.

This expense makes sense when you consider how much content contributes to the overall pipeline. Respondents stated that the monthly investments they make towards content creation reaps significant rewards. Although responses varied greatly, most of the experts cited that around 30-40% of the pipeline is influenced by content creation and distribution.

Creating valuable content for prospects is almost entirely dependent on content analytics. Content analytics offer your sales and marketing teams multiple benefits:

• Helps marketers redefine their strategy based on how current content is performing
• Calculates the ROI for each piece of content, which in turn guides future content strategy and content repurposing.
• Superior prospect experience by focusing on the most relevant content and elimination of guesswork
• Quicker and easier conversion for prospects by offering them content that is relevant and important for them at each stage of the funnel
• Cuts down on redundant content by immediately finding out when certain pieces are underperforming

How can content analytics contribute to a better customer experience?

Understanding each interaction a prospect or customer has with your website and other marketing collateral enables you to improve your content offerings. You’ll be able to offer customers a far better experience by analyzing and iterating based on content data. Content analytics helps you:

Offer relevant content

You can offer clients valuable content depending on where they are in the conversion process. Content analytics help you anticipate which content is relevant at every stage of the funnel, thereby streamlining communication with prospects and clients alike.

Address specific client needs

You can also create a 360-degree buyer persona for existing clients. An integrated analytics software like Factors allows you to have a holistic overview of each client so you can see every interaction they’ve had with your company. You have access to each touchpoint and all their past behavior, thereby enabling you to make educated guesses about their pain points.

For instance, let’s say you run a company that creates CRM software. You could find through trends in content analytics that customers from the tourism industry are interested in the customer service features it offers. On the other hand, customers in the tech industry are more interested in its customization and workflow automation features. You can then use these trends to offer them content that best fits their needs.

Hyper-personalize your content

Prospects today expect a highly customized experience tailored to their needs. It’s essential to curate a personalized experience in order to create a lasting client relationship. Understanding which channels your client base uses, the keywords they’re interested in, and the time they spend trying to solve a pain point on a webpage are all crucial to personalization.

Make better decisions

Content reporting can help you make deeply informed decisions with respect to pricing, sales, organizational goals, and communication. You’ll never have to rely on guesswork again; all you need to do is gather user data through an analytics tool and leverage it relentlessly.

Your clients have needs that are continuously evolving, so you have to continuously utilize real-time data to create adaptive strategies that help you get the most out of your investment.

What are the biggest challenges of content analytics?

Customers’ preferences and expectations from content are constantly changing. Jess Cook from LASSO puts it best: content analytics isn't an exact science. Here are the biggest challenges that marketing and sales teams encounter in the process of analyzing content data:

Data silos

Your sales and marketing teams need access to a unified customer data infrastructure. End-to-end account journeys are of the utmost importance when you’re streamlining the sales and marketing processes. If your sales and marketing teams work independently of each other, there’s a huge chance that they have access to disconnected data.

Data silos lead to an underwhelming customer experience. The sales team should have access to all the marketing touchpoints the user has been through to avoid repetition, tedium, and misunderstandings in the sales process.

Visitor identification

De-anonymization is crucial to effective analytics, since you need to see how many unique visitors your website is drawing and the firmographic characteristics of these users such as company name, industry, employee range and revenue range. However, all users on the internet want anonymity, and there are laws to protect user data from illegal tracking.

Free content analytics tools have limitations

Tools like Google Search Console (GSC) offer users limited insight. Saffia Faisal at Userpilot believes that GSC is inadequate for dedicated content analytics and reporting. B2B companies require an in-depth analysis of how their content is performing. GSC’s algorithm limits accuracy in reporting, providing just a signal of how content performs. GSC also imposes limitations on the number of rows of data that can be exported at a query level.

How content analytics works in Factors

Factors.ai connects the dots between web sessions and CRM events to answer this question through automated form captures, customer journey funnels, and AI-powered inflection analysis to determine what content is helping/hurting larger objectives

“How are my website resources driving form submissions, MQLs, SQLs, Opportunities, Deals, and ultimately, Revenue?" 

Content marketers and sales strategists need access to real-time, relevant data that provides a holistic overview of content and customers alike. These insights can help tailor new content based on what works, thereby driving greater revenue.

Customizable dashboards

Remember the data silos we mentioned earlier? They slow down the progression of the accounts into the sales funnel and may lead consumers to drop out of it altogether. With Factors, however, you have all your customer information present on the same dashboard. Your sales and marketing teams will have access to consistent information, and will be able to see all your clients’ touchpoints. You can choose which metrics you want to view on the dashboard.

Easy account identification

With Factors’ reverse IP lookup, you’ll be able to identify which companies are interested in your solutions through their website visits. If an individual in a company visits your website, Factors will match its IP address within its existing database and identify the company name and domain, industry, annual revenue, and employee headcount. Since the database relies on publicly available data and the data you draw from your website, this process is fully compliant with user privacy protections.

You’ll also be able to see which stage of the funnel a particular prospect is at by the type of content they consume. Once you know the identity and needs of your prospects, you can target them in a personalized manner.

Automated analytics and attribution

Your sales and marketing teams won’t need to crunch numbers or look for missing information. Factors provides all the data you need, such as time on page, page load time, button clicks, scroll percentage, and page views. By automating the process of content data collection, your teams can focus their energies on strategizing and creating quality content for clients.

Factors’ multi-touch attribution model helps your company understand the customer journey and give credit to the touchpoints involved in the conversion process. It provides more detail with respect to user behavior when compared to single-touch models. A multi-touch attribution model aims to highlight which touchpoints have the greatest influence in the account’s journey, and how they work together.

Adaptation based on new insights

Your customers’ requirements are constantly evolving. It’s necessary for your analytics and attribution systems to respond to these nuances. Factors allows you to obtain instant insights about which content assets are redundant or performing well. You can use these content performance reports to refresh older content and push pieces that are doing well across more channels.

Get in touch with us today to find out how Factors can help your company improve its content analytics and reporting.‍

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Dive in Deep with Factors

Factors.ai takes content analytics one step further with extensive breakdowns + filters, custom dimensions + KPIs, and Content Groups.

 As a content marketer, you may be interested in granular insights into your resources. “What geographies are consuming most of my work?”, “Is my blog being read more frequently on a phone or on a desktop? Should I optimize accordingly?”, “What campaigns, channels, and sources is web traffic originating from? “What about my SEO efforts and organic traffic?”.  

Factors.ai answers these questions and more with an extensive range of filters and breakdowns. Additionally, there’s ample flexibility to create your own custom events and KPIs if you’d like to track tailor-made metrics.

Finally, with Content Groups, you can group a collection of logically related URLs that make up your overall website content. For example, core web pages like “features” “pricing” and “product” may be defined under one group to measure holistic performance. Similarly, blog articles written with specific intent can be analyzed all in one go. No doubt, a handy feature for content marketing analytics.

FAQs

How do you use analytics in content marketing?

Content analytics include reporting on website, marketing, and sales metrics. Understanding how customers interact with your content allows you to personalize your marketing campaigns in order to drive more conversions. Measuring these metrics also helps you address specific pain points and therefore improve the overall consumer experience for your solution.

Which metrics should I measure for content performance?

We asked experts about the metrics they keep track of to ensure high content performance. Their responses included clickthrough rate, impressions, marketing qualified leads, scroll depth, time on page, unique visitor identification, downloads, funnel movement, influenced demos, and bounce rate.

And there you have. Our customers regularly use Factors.ai to make sense of their content performance and guide their B2B content marketing strategy with the help of granular web page analytics, end-to-end customer journey insights, and flexible content reporting. If you’d like to learn more about our work at Factors, schedule a personalized demo today.

GA4: End Of The Road For Google Analytics?

Over the last decade, Google Analytics has dominated the marketing analytics space. This uncontested reign can be attributed to a couple of key reasons: One, GA is free. And two, GA maintains a monopoly over historical data for an enormous install base. While the former isn’t likely to change, the introduction of GA4 is set to crush 10+ years of backward compatible data for millions of websites — including yours.

By breaking history and forcing a migration from Universal Analytics to GA4, Google Analytics loses an important advantage. This, coupled with a host of issues around UI, functionality, and privacy has resulted in a dramatic turn in tides. If users are going to lose out on their historical data by next year anyway, there’s little incentive for them to stay — especially when the best Google Analytics alternatives are readily available.  

“We will begin sunsetting Universal Analytics — the previous generation of GA —  next year. All standard UA properties will stop processing hits new hits on July 1st, 2023” - GA Support

“GA4 feels like a huge step backwards. Tons of functionality in the previous version is missing or replaced with smart “insights” — which always goes wrong. A good time to move on to something better” - Hacker News

With this in mind, The following article compares Google Analytics (specifically, GA4) with Factors to demonstrate why, now more than ever, the latter is better suited for B2B marketing analytics, web analytics & CRO, multi-touch attribution, and more. 

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Data Integration

To be of any value, B2B marketing analytics requires substantial data from a wide range of sources. This includes granular metrics across all your ad campaigns (Google, Bing, Facebook, Linkedin, Capterra, etc.), website, and CRM (HubSpot/Salesforce) events. Ideally, this body of information is unified under one platform to ensure normalized data and alignment across demand gen teams. So how does Factors compare with Google Analytics when it comes to data integration? Here’s the rundown:

Ad Campaign Metrics

Google Analytics can report basic traffic data from most commonly used social platforms — Google Ads, Facebook/Meta, Linkedin, etc. Integrating non-Google sources, however, is significantly more challenging on GA. It requires the construction of custom campaigns using URL builders (read: a time-consuming, laborious chore). Factors, on the other hand, deliver immediate no-code integrations. 

The real issue with GA, however, is that it cannot pull metrics that matter from any source that isn’t Google Ads. Commonly tracked figures like impressions, engagement, click-through rates, etc cannot be reported, let alone linked with website or CRM data. This is a headache for users looking to consolidate all their marketing efforts under one roof. Factors solves for this by automatically pulling granular metrics across the board.

CRM Integration

This is another big point for Factors. Unlike GA, Factors provides robust integrations with HubSpot, Salesforce, and soon, Leadsquared. The implications of this are significant. Marketers will have the ability to connect the entire customer journey from first touch to deal won. In turn, marketers can determine exactly how their efforts across ad campaigns, web content, and offline events are contributing to larger business objectives like pipeline and revenue. This is simply not possible on Google Analytics as it does not integrate with any CRM whatsoever.

Third-party Integrations

Another reason Factors has the edge over Google Analytics is third-party integrations. Factors integrates with the likes of Clearbit Reveal (Deanonymization), Segment (CDP), Drift (Chatbot), and more to ensure an actionable web + marketing analytics experience. Again, this is impossible on Google analytics because GA4 does not integrate with third-party platforms. Consequently, this affects the quality of customer journey insights. Even with sophisticated manual analysis, the data derived from Google Analytics is likely to remain superficial at best. In later sections, we’ll explore the implications of this issue in detail. 

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Implementation & Onboarding

So far, we’ve established that data integration (including third-party) makes more sense with Factors. Next, let’s examine how the two marketing analytics tools compare with regards to implementation and onboarding. For context, if you’re currently using Universal Analytics, you either have to upgrade to GA4 by next summer (June 2023) or find a GA alternative like Factors. 

What does it take to upgrade to GA4?

12-steps. That’s right. It requires 12 steps before you can upgrade from Universal Analytics to GA4. What’s more? As previously mentioned, integrating with non-Google ad platforms needs elaborate orchestration with custom campaign URL/UTM builders. Additionally, GA4 requires users to manually tag each event they want to track. In short, this means significant labor effort, engineer dependency, and time-spent waiting for incomplete datasets.

What does it take to set-up Factors.ai?

Maybe about 30-min. In fact, it’s probably closer to 10 with Google Tag Manager. Simply place the superlight SDK onto your website and integrate (no-code!) with your ads platforms, CRM, CDP, Chatbot, and more. Before you know it, all your marketing + web data will begin pouring into a single, normalized platform. Easy as pie.

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B2B Marketing Analytics

Now, let’s discuss functionality. Here’s how Factors compares to Google Analytics when it comes to core use-cases of a B2B marketing analytics tool.

Right off the top, it should be noted that GA isn’t built for B2B marketing analytics. It struggles to support tracking for journeys that involve several months, touch-points, and stakeholders. Unfortunately, these are the precise characteristics of a standard B2B sales cycle. Customers often experience countless (well, on average, 7) touchpoints — both online and offline — across ads, emails, webinars, blogs, web sessions, etc before converting. These touchpoints can occur within a window of one week, one month, or sometimes, even longer than one full year. Unlike Factors, GA4 isn't designed to analyze or attribute lengthy, sporadic interactions for B2B marketers. 

Additionally, and as previously mentioned, GA is unable to track and measure granular campaign or event metrics from non-Google platforms. Since B2B marketers target (and retarget) marketing efforts to their audience across several channels, it’s nearly impossible to consolidate these figures on GA alone. 

Factors eliminates this data silos issue for marketers and demand gen folk with the help of aforementioned third-party integrations. Once data has been collected, Factors delivers an end-to-end marketing analytics suite that’s tailor-made for B2B teams.
This includes web analytics, funnels, custom events and KPIs, multi-touch attribution and more. Let’s explore why Factors has the edge over GA across these use-cases.

Data Accuracy, Marketing Funnels,
Revenue Attribution, & More

At its core, Google Analytics is a website analytics service. And to be fair, GA does a half decent job at it, especially for a free tool. That being said, there are significant limitations with GA that Factors solves for:

Data Accuracy

‍Certain web metrics are not precise on GA. Let’s say a lead lands on a blog on your website. Before they can start to read the article, their doorbell rings and they leave to answer with the blog page open on their laptop. The lead returns in about 8 minutes, clicks out of the blog to schedule a demo. Google Analytics would inaccurately assume that the blog played a massive role in this conversion because of the significant (8 min) time spent on page. In reality, however, the lead did not scroll even a little to read the rest of the piece. Factors solves for such issues by tracking granular details like cursor activity and scroll depth percent to ensure your data, and the insights derived from that data, is as accurate as can be.

Marketing Funnels

‍On GA4, you’re limited to page-to-page funnels. That is, GA4 only considers funnels wherein each webpage is a separate step. As such, GA4 struggles to track multi-session engagement. Let alone a funnel across ads, web, and CRM. Funnels on GA may only be used to reliably measure drop-offs and conversions that occur in the length of a single web session (Eg: Blog -> Pricing -> Schedule Demo in one web session). Additionally, event funnels are not supported on GA4. Hence, if you’d like to track how specific website content is contributing to MQLs, leads, & revenue, GA4 won't suffice. 

Customer Journey + Revenue Attribution

As previously mentioned, GA does not integrate with CRMs like HubSpot, SalesForce, or Leadsquared. This severely impedes cogent customer journey analysis and revenue attribution. Without laying the entire map from ads, offline efforts, web sessions, and CRM events, you are left with an incomplete picture of what’s driving revenue and pipeline. Consequently, this affects data-driven decision making, which ultimately results in suboptimal marketing strategy and ROI. It is not feasible to derive end-to-end marketing insights into what’s working and what’s not with Google Analytics. While GA might be able to track the source of traffic, it cannot determine the cause.

Usability - UI and UX

What’s surprising  is that even with these significant drawbacks, users complain about GA4’s useability. It can be overkill — unintuitive, excessive, and far too technical — for marketers looking for basic reports. And completely irrelevant to marketers looking to dig deeper into their data. Let’s let twitter expand upon this…

Website owners, is it just me or is the new GA4 just HORRIBLE? It's like it's designed only for retail sites or something, very hard to get the basic info that I used to rely on... Think I'll switch back! Awful!

Trevor Long (@trevorlong)

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)

1. The UX of Google products in general suck
2. GA4 is a new level of suckiness
3. I get the feeling Google doesn't have a UX team and/or never tests the usability of their products
4. If you are not a monopoly you would never be able to get away with this

Tom Kasperski (@TomKaz)

Factors is simple by design. Users go from onboarding to creating powerful (and basic) marketing reports in a matter of minutes.

Now Is The Best Time to Switch Over From Google Analytics To Factors.ai

And there you have it. A non-exhaustive set of reasons as to why Factors.ai makes far more sense for B2B marketers over Google Analytics. With the imminent arrival of GA4 (and the consequent break in years of historical data), now is the best time to make the move to Factors.

Customers are complex. What drives them? What bothers them? What encourages them? And what convinces them to choose you over your competitors? Without a clear framework in place, answers to these questions remain nuanced and theoretical. 

Here’s where customer journey mapping can help. 

A customer journey map visualizes the entire customer experience with your company — from awareness to deal won, and sheds light onto why your customers behave the way they do at every stage of the sales cycle.

As we will see, customer journey mapping proves to be beneficial in acquiring more customers, faster — and retaining them for longer durations of time. 

Here’s what this guide to customer journey mapping covers:

1. What is customer journey mapping?
2. How does customer journey mapping work?
3. Why do B2B companies need to map out their customer journeys?
4. What should you include in your customer journey map?
5. Steps to create a customer journey map
6. Customer journey map vs user experience map: what’s the difference?
7. How does Factors.ai help with customer journey maps?

What is customer journey mapping?

Especially in B2B deals, customers rarely make purchase decisions on an impulse. Instead, they spend significant time identifying pain-points, researching solutions, comparing alternatives, and freeing up budgets before finally becoming paying customers.

Customer journey mapping can be defined as the visualization of interactions that a buyer has with a company across the entire sales cycle — from awareness to deal won to retention. Customer journey mapping provides valuable insights to refine the overall customer experience, drive conversions, and improve customer retention rates. 

In short, the customer journey map encapsulates this buyer experience. This journey can be broadly divided into: pre-conversion, onboarding, and post-conversion. 

Each of these segments can be further broken down into granular customer touchpoints that the marketing, sales, customer success, and product team are responsible for. 

How does customer journey mapping work?

There’s no one right way to go about customer journey mapping. But at its core, customer journey mapping works by consolidating and visualizing an otherwise complex, non-linear sales cycle.

With this framework, go-to-market teams can identify how customers behave, what their preferences are at each stage of the sales cycle, and what helps or hurts conversions. 

As you might have guessed, plotting this customer journey map involves compiling data from a wide range of touch points across the sales cycle.

Without the right tools and techniques, tracking these touch-points across channels, campaigns, offline events, website, CRM and more can be a daunting task. More on how Factors.ai can ease this process later. 

What should you include in your customer journey map?

While every business involves its own unique customer journey, a few key elements remain constant across the board. Here’s a breakdown of what you should look to include in your customer journey map.

1. Sales Cycle

Firstly, connect the dots between relevant data sources across campaigns, website, MAPs and CRM. This is to understand where your customers are coming from and how they’re engaging with your brand across the sales cycle. 

The average B2B sales cycle can be broken down into the following stages: 

1. Awareness (ToFu marketing, branding, etc)
2. Consideration (BoFu marketing, sales discovery, trials, etc)
3. Decision (Effective sales and customer success)

2. Customer Behavior

Based on the data collected from the previous point, gauge how customers behave at different stages of the sales cycle. 

Let’s say that the data suggests that during the awareness stage, buyers look to learn more about the problem they’re facing. At this stage, educational material such as ebooks or webinars may be more relevant to customers as compared to bottom of the funnel material such as comparison articles or case-studies. 

3. Sentiment

B2B deals tend to be perceived as unemotional, objective transactions. However, at the end of the day, B2B businesses still sell to people — buyers and users — within a business. Accordingly, it’s important to consider the sentiment of leads and buyers during every stage of the customer journey. 

For instance, the problem-awareness stage may involve frustration or confusion that we should look to minimize with useful content and personalized outreach. The solution-decision stage may involve feelings of relief or happiness which should be maximized with reliable customer support and relevant documentation. 

4. Problems

Carrying on from the previous point: For any negative sentiment, there’s probably a pain-point or problem behind it. Identifying these pain-points at various stages of the customer journey will help create pointed, relevant customer experiences that look to solve user problems.

5. Solutions

As previously mentioned, we can look to solve challenges and paint-points along the customer journey to reduce or eliminate any points of friction. This will ensure smooth sales conversions.

Why do B2B companies need to map out their customer journeys?

Creating a customer journey map, especially without the right tools, can be an unintuitive and daunting task. Why then should businesses care to go through all this effort? 

The overarching reason for B2B teams to create customer journey maps is because of its positive impact on customer experience, conversion, and retention. Breaking down the customer journey into broad stages with individual objectives simplifies, and ultimately improves, an otherwise convoluted customer journey. 

Here are a few specific ways in which customer journey mapping benefits the customer experience, which in turn benefits your businesses’ bottom line metrics.

1. Identify what resonates with your audience 

Customer journey mapping helps identify how different messaging, content, topics and themes resonate with your target audience. While marketers tend to have a hunch about this, qualifying a hypothesis with data helps scale efforts confidently.

2. Refine personas and improve targeting

Targeting a broad audience isn’t effective or scalable in the long run. Customer journey mapping sheds light onto which customers are actually interested in the value of your product. This helps refine the characteristics of ideal customer profiles and allows marketing teams to go after targeted, high-intent audiences. 

3. Improve customer retention rate

The customer journey map charts a course all the way into the product and its end-users. This provides valuable insights into who the product is helping most, and how it’s helping them. 

With this end-to-end view of the customer journey, it’s clear to see where to improve the customer experience, even within the product. This is invaluable information given that a third of Americans consider switching to an alternative after a single poor experience.  

Ultimately, improving the customer experience means improving customer retention. Which in turn lends itself to stronger pipeline and  up-selling opportunities.

Steps to Create a Customer Journey Map

Here’s a step-by-step breakdown of creating a customer journey map from scratch.

1. Define customer journey objectives 

The first step is to determine why you’re constructing a customer journey map. What’s the objective? Whose customer experience are you looking to improve? Based on this information, define 1-3 hypothetical buyer personas that represent your ideal customer profile.

Buyer personas should be based on a combination of firmographic features like industry, revenue, and headcount as well as user-specific characteristics like role, department, tech-stack, etc. 

2. Survey prospects and customers 

After defining your hypothetical “perfect customer”, it’s time to survey your actual prospects and buyers. This is mainly to close the gap, if any, between how you believe your customers think and how they actually think. 

Here are a few questions to ask prospects and customers:

• How did you hear about us?
• What are you looking to solve for? What’s your biggest pain-point?
• How would you rate our onboarding process on a scale from 1-10?
• How do you think we can improve our website content? 

3. Track customer journey touchpoints

While asking customers where they found us and how they like our product is all well and good — it’s rarely sufficient. For one, B2B sales cycles last several weeks, if not months. It’s hardly fair to expect customers to remember the exact social media post that drove them to your website. 

For another, subjective interviews are often riddled with bias and leading questions. To avoid inaccuracies in data, it's crucial to independently track touch-points across campaigns, websites, MAPs, CRM, and other relevant sources for objective analytics. With this, we can find answers to questions like:

• Which channel is driving the most traffic to my website?
• Which blog topics lead to the most conversions? 
• What percentage of the pricing page are visitors scrolling through? 
• How are customers progressing from an ad campaign, to website, to demo, to deal won?

Consider the sentiment, pain-points, and solutions that are associated with every customer action in order to understand motivations and tailor marketing efforts efficiently. 

For example, if a page on “Identifying website visitors” seems to be driving a lot of conversions, this may be a pressing pain-point or use-case to your audience. In this case, tailoring outbound efforts and organic social with more content on visitor identification may be fruitful. 

4. Allocate resources across the customer journey  

So far, we’ve defined who we want to sell to, identified what current customers are thinking, and tracked how these customers are interacting with our brand. 

Based on this goldmine of information, we receive a rough idea as to how we can better allocate resources. For instance, maybe mapping out this data reveals that webinars seem to perform disproportionately better than paid social at driving high-intent visitors. 

Alternatively, this customer mapping exercise may also reveal a dearth in specific tools that could help accelerate sales velocity – email automation, customer service management, etc. 

The reallocation of resources that follows these insights will ultimately result in the first iteration of the customer journey map. A design that encapsulates who your ideal buyers are and the ideal path they’ll take to become paying customers.

5. Analyze the customer journey 

At this stage, we’ve crunched a whole lot of customer data and allocated resources to optimize the customer journey. But this is just one half of the puzzle. Analyzing and iterating based on real-life results is crucial to the success of a customer journey map.

Look to answer questions like:

• Where are customers dropping off disproportionately? 
• Which touch-points are driving higher-than-average conversions? 
• How does the quality of leads differ from one channel to another? 

This is where the customer journey map graduates from theory to practice. 

6. Iterate. Iterate. Iterate. 

Using learnings from the analyses of the customer journey, run a wide range of experiments to test specific hypotheses at every stage of the sales cycle. 

Perhaps reworking ad copies, repositioning CTAs on the website, investing in a customer service tool, updating the onboarding flow result in improved customer experience and conversions.

Rather than relying on intuition or guesswork, use the customer journey map to identify and iterate on strengths and limitations with data-driven insights. 

Ideally, the customer journey map should be revised every month or quarter to stay aligned with every-changing customer behavior.

Customer Journey map vs User Experience map: What’s the difference?

In short, a customer journey map considers every measurable interaction that a customer has with your business from awareness to consumption. A user experience map, on the other hand, only considers how customers use the actual end product. 

It’s important to distinguish between the two because, especially in B2B deals, the buyer is often different from the end-user. While there’s generally significant overlap between the two concepts, user experience is a subset of customer experience. 

For example, a CMO reads a blog and attends a demo through a website before purchasing your software for her content marketing team. While the CMO might be thoroughly impressed with the material she’s interacted with, the content marketing team may actually be disappointed with the software.

While a customer journey map will consider this case end-to-end, a user experience map will only highlight the limited usage of the software by this content marketing team. 

How does Factors.ai help with customer journey mapping?

Here are four ways in which Factors.ai can help map out your customer journey:

1. Account and User timelines

Factors unifies customer journey data across campaigns, website, and CRM to present an interactive timeline of touchpoints at a user and account level. This is an especially powerful tool for account-based marketing teams to track how users from their target accounts are progressing through the sales cycle.

2. Account Identification 

Factors uses industry-leading IP-look up technology to identify up to 64% of anonymous website traffic.. This provides valuable insights into which accounts are visiting your website and how they’re interacting with pages and content. 

This firmographic and intent-data helps shape the buyer personas for your customer journey map as it sheds lights onto how different types of companies  interact differently with your brand.

3. Attribution

As previously mentioned, measuring the right touchpoints and tying it back to revenue manually is, to say the least, a chore. Multi-touch attribution on Factors helps connect the dots between conversions and pre-conversion touchpoints. Compare a range of attribution models based on the nature of your business to quantify the impact of marketing effort on pipeline and revenue.

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4. Path analysis

Path analysis is similar to timelines in that it provides an intuitive visualization of various accounts and users traveling through different paths along the customer journey. The difference is that path analysis reflects aggregated user behavior rather than a specific account’s journey.

This is helpful when testing hypotheses, running experiments, or gauging customer behavior on a larger scale. 

And there you have it! A complete guide to customer journey mapping — and how Factors.ai can help construct your customer journey map.

We’re thrilled to announce our partnership with industry-leading account-based marketing platform, 6sense. 

With this deep-rooted collaboration, Factors.ai now delivers state-of-the-art account identification, firmographics, and intent data along with our existing ABM analytics and attribution capabilities.

Users can expect to tap into 6sense’s extensive databases with Factors.ai to discover upto 64% of anonymous companies visiting the website — including account-level website behavior, purchase intent, and timelines. 

Account Identification + Account Analytics = ABM Magic

This article highlights what the partnership means for our users, along with a few use-cases and testimonials. If you can’t already tell, we’re really excited for the immense value this collaboration brings to our customers.

A few common questions

Why partner with 6sense over other alternatives?

Rigorous comparative testing with over 20,000 IPs reveals that 6sense is far ahead of the game in terms of data quality, volume, consistency, and pricing. The infographic below highlights 6sense's ability to identify up to 27% more accounts than the closest alternative. Also, it doesn't hurt that 6sense is one of the leading ABM platforms in the market today.

Do users need a separate 6sense account to use account identification with Factors?

Nope! you do not have to be a 6sense customer to use account identification with Factors. Simply reach out to our team to enable this integration within your Factors project — without signing up or paying independently for a 6sense account.

If you are an existing 6sense customer, simply integrate your 6sense account to Factors using the API key.

Can Factors identify email IDs or phone numbers of anonymous website visitors?

No. Factors is a privacy-first, GDPR compliant solution. It only discovers IP-to-Company-level data. Factors does not identify individual website visitors or personal information like phone numbers or mail IDs unless the user chooses to share this information through form submissions.

How does pricing work?

Read more about our pricing details here: factors.ai/pricing

6sense & Factors.ai: What’s in it for you?

As B2B go-to-market teams continue to adopt account-based marketing strategies, there’s a growing demand for both account analytics and account intelligence. Here’s how the 6sense x Factors.ai partnership helps with both:

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Factors's real-time Slack Alerts for accounts identified via 6sense's visitor identification technology have helped our Sales Team be proactive. Roughly 25% of last month's new revenue for Clearfeed is due to the outbound outreach done by the SDRs based on Factors data.

1. Account Identification

B2B companies invest significant resources towards driving high-intent website traffic. Unfortunately, only about 4% of this traffic comes to light through forms or signups. With 6sense, Factors.ai can identify up to 64% of anonymous companies using industry-standard IP-lookup technology! 

As we’ll cover in following sections, this provides sales and marketing teams with the ability to identify and target the right opportunities, personalize the customer experience, and measure the impact of campaigns.

2. Firmographics + Advanced Analytics

In addition to identifying company names, 6sense enriches visitor data with detailed firmographics such as domain, industry, headcount, location, and more. This information is continually optimized with proprietary machine learning and human QA. Firmographic data, in conjunction with Factors.ai’s advanced website analytics — button auto captures, page time spent, scroll percent, etc — helps effectively identify high-intent accounts, well-resonating website content, and points of friction along the customer journey.  

The cherry on top: configure real-time Slack alerts when target accounts land on specific web pages to reach out to leads while the iron’s still hot. Research finds that contacting leads quickly significantly improves the odds of conversion. Our early adopters have been seeing real value delivered to their sales reps and ABM marketers.

3. Account Journeys & Timelines

A crucial element of account-based marketing is tracking how target accounts are progressing along the customer journey. Upon identifying companies visiting your site, Factors.ai creates an intuitive account-level timeline of the journey in real-time — across campaigns, website, and CRM. 

On one hand, this provides retrospective insight into what campaigns and assets drive conversions. On the other hand, it provides forward looking inputs to optimize retargeting efforts and personalize sales pitches based on the account’s previous interactions. 

Struggling to identify more than 5% of your anonymous traffic? See how Factors.ai can help your business reveal upto 64% of website traffic over a personalized demo.

Use-cases: Account Identification, Firmographics, and Intent Data

1. For Demand Gen

With this partnership, demand gen teams can see which marketing initiatives and assets are driving high-intent accounts to their website. Rather than relying on expensive spray and pray tactics, teams can reallocate resources to targeted efforts that bring in the right kind of buyers. 

On the flip side, demand gen folk can reveal companies visiting the website  and retarget the right, ICP accounts based on firmographic and intent. In a time when teams are asked to do more with less, Factors offers to optimize marketing ROI and make tight budgets go a long way. 

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A game changer for B2B Marketers for Account Analytics. Factors' advanced analytics combined with 6sense visitor identification allows us to build a complete understanding of the Account Journey including the dark funnel. We are now able to plan our marketing campaigns and content efforts with clear visibility into what is driving conversions and pipeline.

2. For Content Marketers

B2B companies tend to invest heavily in content without actually knowing who the end consumers are. With Factors, content marketers can pin-point who’s reading ungated assets such as blogs and case studies. 

For one, this helps discern what content resonates with different audiences. Content teams can guide their strategy based on what resonates best with their target personas. For another, content marketers can tie their efforts back to bottom line metrics like pipeline by showcasing timelines as buyers progress from blogs, to demos, to trials, and finally, to deals.

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Combining 6sense visitor identification with Factors' advanced analytics has unlocked insightful views for our product and content marketing teams. We now have a clear view of how our content performs across key audience segments — and the opportunities to optimize user journeys and conversions further.

3. For Product Marketers

Product marketers continually iterate on messaging for core pages such as the home page, pricing page, and features page. While standard web analytics and A/B testing tools provide insight into whether a certain message is working for overall traffic, this partnership empowers product marketers to experiment and tailor messaging for known visitors. 

For instance, account identification and firmographics may reveal that larger companies are more interested in privacy compliance material while smaller teams may care about transparent pricing. Based on who the PMM is looking to target, they may alter messaging accordingly. 

4. For Sales

The benefits of account identification and analytics is especially apparent in the case of sales teams. For one, sales reps can tap into a net-new pool of business from existing website traffic with zero additional spend. Within this set of accounts, sales can target the right ones based on intent and engagement insights. Finally, rather than spending hours trying to contact cold prospects, sales reps can improve direct engagement by reaching out to accounts while they’re on the site through real-time Slack alerts. 

Overall, the workflow encouraged by the 6sense x Factors partnership dramatically improves sales productivity.  

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A dream solution for B2B marketers to unfold user journeys. When we chalk plans for a campaign, we love valuable insights. Even better when I have it diced & sliced. We get it all here & engage with our audience. The granularity of data is perfect & the mining engine of Factors with 6sense has unbelievable match rates for de-anonymizing accounts.

Curious to see 6sense and Factors.ai in action? Book a personalized demo here!

Related reading: 

1. Identify anonymous accounts visiting your website with Factors.ai
2. Website account identification

I recently came across an article that placed a great deal of emphasis on getting your definitions right. Of course, ‘defining’ things — roles, processes, objectives — holds plenty of value. From providing clarity and purpose to qualifying breakthrough ideas, a good definition can help teams go a long way in reaching their goals. And yet, even the most precise definitions are bound to change. 

With that in mind, this post discusses the elements that define the new and improved Revenue Marketer. In particular, we explore six pillars of Revenue Marketing and highlight the value of data, technology, and organisational alignment in effectively driving revenue growth.

But first, let’s quickly run over the fundamentals of Revenue Marketing.

Like many others, I learned about the term 'Revenue Marketing’ through Dr. Debbie Qaquish. About 10 years ago, during a transition from a long career in sales to a role in marketing, her CEO sat across her desk and posed a single question: “What are you going to do about revenue?” Long story short, this set off the development of a significant approach that transforms marketing teams from flowery cost centers to high-performing revenue machines. This approach, we've come to know as ‘revenue marketing’.

“Revenue marketing is the combined pillars of strategies, processes, people, technologies, content, and results across marketing and sales that drop leads to the top of the funnel, accelerates sales opportunities through the pipeline, and measures marketing based on repeatable, predictable, and scalable contribution to pipeline, revenue, and ROI” 

Phew. 

That was a mouth full. 

Now don’t get me wrong; this continues to remain the foundation upon which Revenue Marketing is built. But back then, the market looked very different from what it is today. We’ve had major changes that mandate an updated definition of revenue marketing. Accordingly, here are three additional challenges that redefine what it means to be a revenue marketer today.

Challenge #1 - Digital transformation

In 2011, the average number of technologies available to the marketing industry was about 150. Today, that same measure stands at an astonishing 7000. It’s becoming increasingly normal for marketing teams to employ upwards of 30, or even 40 different pieces of MarTech products. But digital transformation isn’t just about getting your hands on the hottest new tech toy. Now, Marketers have to choose between all-encompassing platforms like SalesForce and specialised best-in-class solutions for each use-case. The key challenge here is to centralise customer data and orchestrate these platforms to deliver a personalised customer experience. 

Challenge #2 - Customer centricity

It's no secret that as an industry, marketing has been progressing towards customer-centricity. Now more than ever, a firm’s customer experience signals its competitiveness in the market. Again, at the root of this change is digitalisation and technology. Digital customers are in control because your competition is now a single click away from you. Accordingly, identifying and employing the appropriate marketing channels — and distributing relevant content within those channels becomes a key challenge. 

Challenge #3 - Revenue accountability

A 2019 report by Duke University found that 80% of CMOs are under pressure to deliver ROI, revenue, and growth. However, only about a third provide any financial reports as a result of technological inaccessibility and an overall lack of training. Though we have countless programs and platforms to crunch marketing data and derive revenue metrics, they can be a little too inaccessible for marketers without analytical backgrounds to make effective use of. 

And so, we arrive at three challenges — each one based to varying extents in data, technology, and alignment  — that are driving the new definition of revenue marketing.

The new and improved Revenue Marketer 

Teams in leading B2B companies continue to transform themselves from cost centers to predictable and scalable revenue machines. Except now, they have an additional focus on digital transformation, customer-centricity, and revenue accountability. As an outcome, marketing is driving non-linear growth in a world where buyers are averse to direct sales.

Okay - so far, we’ve established our basis for the contemporary definition of revenue marketing. But let’s go even further. Not only is data, technology, and alignment fundamental in defining revenue marketing; it is essential to every capability within every pillar associated with the approach as well.

Strategy

In revenue marketing, strategy involves understanding your team’s readiness for change, aligning your company’s key business initiatives, and most importantly — forming revenue synergy with sales. While a large part of this ‘getting everyone on the same page’ process involves planning, communication, and leadership; technology is playing an increasingly important role as well. Though instinct and qualitative responses can complement strategy, data, metrics, and indicators are crucial ingredients in developing accurate customer profiles and journeys. And as all three merge across sales and marketing, teams require ecosystems that are conducive to a symbiotic, well-aligned workflow. An easily accessible analytics platform (*ahem* Factors.AI) enables sales and marketing folk to speak the same language — revenue.

//Factors.AI is an AI-powered marketing analytics platform that provides critical insights into your marketing activities, decodes customer behaviour, and empowers your marketing team to focus on real strategic decisions. In short - we do all the analytical heavy lifting for you.//

Process

The process pillar isn’t dissimilar to traditional marketing. In general, Process primarily involves campaigns and data. Accordingly, there are two aspects worth highlighting — campaign management and data management.

Campaign management involves executing, tracking, analysing, and measuring digital conversions in terms of business impact. There has been tremendous progress in the MarTech space within each of these functions. Not simply to automate the process, but to derive detailed insights as well. It’s a similar story with data management. Easy access and insight into your marketing data can make all the difference in the world. Implementing this process could be as simple as consolidating all your data under a single roof or automating any recurring analysis.

//Factors.AI enables your marketing team to consolidate and crunch marketing data from across all your sources - Google, Linkedin, Facebook, and more. Our integration process is completely code-free as well. In fact, we could have your marketing team onboarded in a single week.//

People

The people pillar consists of broad capacities involving the management of people in and outside of marketing. Stakeholder alignment, resource planning, and talent acquisition are important, but talent management in particular, is an aspect worth highlighting. A firm can employ all the data and technology in the world, but if the marketing team doesn’t have sound control over these tools, they won't be of much use at all. One solution to avoid this issue is to keep things simple.

//Factors.AI is simple by design. Our platform has been tailored to make the user experience very, very intuitive. In fact, our AI-powered analytics platform does all the work behind the scenes, so detailed insights into your data becomes as straightforward as a google search.//

A training program with a specific focus on revenue marketing tools can also go a long way in improving technical fluency and ensuring your team has a good grasp of revenue-oriented data.

Customer

As a revenue marketer, it is important to understand your customer across their entire life cycle. It’s no longer sufficient for marketers to get a customer through the door and call it a day.  Revenue marketing encourages you to keep tabs on all the touchpoints a customer goes through. Additionally, a revenue marketer aims to optimize their customer data - not only to improve campaign performance but to access valuable business insights as well. A second aspect that’s closely tied to the customer is content management. The batch and blast approach simply doesn’t make the cut anymore. It’s just as important for content to be relevant to the intended audience as it is for that content to travel through the right channels.

//Multi-touch attribution, End-to-end customer insights, and Automated analysis are but a few of the several features Factors.AI has to offer. When coupled with highly customisable campaign analytics - our platform makes for a very simple, very powerful marketing tool.//

Results 

Finally, we arrive at Results. Results to a revenue marketer involves a variety of measures associated with financial outcomes (Shocker!). But it doesn't end there. Along with delivering an impressive ROI, revenue marketers also aim to accurately forecast their revenue. In essence, they construct a marketing machine that drives repeatable, predictable, and scalable revenue. I probably sound like a broken record at this point but analysing data, utilising the right tools, and ensuring organisational alignment are crucial elements at this stage. Needless to say, sufficient training and practice won’t do any harm either.

//Factors.AI’s explain feature differentiates us from the rest of the game. Along with consolidating your data and performing automated analytics, our AI-powered platform provides actionable insights in a matter of minutes.//

Over the course of this post we’ve discussed what it means to be a Revenue Marketer today, we’ve briefly explored the six pillars associated with revenue marketing, and we’ve highlighted the value of utilising data, ensuring alignment, and employing the right tools and technologies. At the end of the day, revenue marketing is a pretty straightforward idea — A well-organised, well-equipped approach that empowers marketing teams to bring in money in a predictable, scalable manner. So as a marketer, the only question left to ask yourself is this:

“What are you going to do about revenue?

In 1908, Henry Ford introduced the Model-T to the world with a full-page advertisement in Life magazine. The print ad read like an article and was chock-full of technical jargon by design. Back then, a marketer’s function was straightforward — inform all potential customers of the existence and superiority of the product. Who you were marketing to wasn’t half as important as what you were marketing. As long as buyers in the market were aware of the Model-T’s vanadium steel chassis and four-cylinder engine, Ford’s marketing team could sleep well at night knowing they had done their jobs.

Of course, the role of the marketer has evolved *a little* since then. At the time, print ads were one of the few viable communication channels available to marketers. There was also a stubborn focus on the product itself — with little thought given to what worked for each customer. Owing to years of progress in marketing technology and a radical shift towards customer centricity, marketers today have a lot more to think about. Recent digital transformations have empowered marketers with dozens of channels: social media, email, blogs, videos, podcasts, websites, etc.  In turn, they’re able to reach potential customers with content that’s specifically tailored to them. 

On the other side of the equation, digital transformation has also provided customers with far more control. Relevant market information (product details, reviews, alternatives) is instantly accessible to potential buyers. And when your competitors are a single click away from you, there is no room for complacency. As a result, the modern marketer must go above and beyond traditional information distribution. Today, the four staple functions performed by marketers are: 

• Delivering predictable pipeline and revenue 
• Building the company’s brand 
• Developing long-term growth initiatives 
• And empowering the sales team 
  

Still, as marketing has evolved in terms of technology and practice, analysing data and deriving insights have grown increasingly complex as well. While marketers are able to design sophisticated multi-channel campaigns, determining the basic metrics — what’s working, what’s not, which campaigns to invest in, etc. — can become tricky. Here’s an example to illustrate this: 

Gendesk, a help desk software start-up, takes out advertisements on Youtube and Facebook. Deepti, a customer success VP, stumbles upon the YouTube ad while trying to watch a video of a sleep-talking cat. She takes notice of Gendesk and clicks through to their website. Though she likes what she sees, she forgets to sign up for a demo. Later that week, Deepti comes across the Facebook ad while scrolling through her feed. This time, she ensures to schedule a call and finds the product to be a great fit. After discussing with her team, Deepti decides to make the purchase.  

As a marketer, this is great news. But when you’re looking to repeat this process in a scalable manner, a key question to ask yourself is “Which ad do I credit for the purchase decision?” Though there are cases to be made for each ad, the right answer is a subtle combination of both. Identifying this combination of credit, or in other words; determining the values to attribute to the various touch-points along the customer journey is now the holy grail of marketing analytics.     

Enter: Marketing Attribution

The previous example was based on a highly simplified customer journey — one customer and two channels. In reality, marketers target several types of customers and employ several different channels to engage with their audience. What’s more is that the buyer’s journey is almost never a linear path. Deepti may well have stumbled upon the youtube ad, visited Gendesk’s website, interacted with their chatbot, reviewed the pricing page, read a blog about the product, and clicked back to the website before coming across the Facebook ad and making his purchase. Marketing attribution is a tremendously powerful system that determines these various touch-points along the customer journey and attributes a percentage value to each one of them.   

Okay, but why’s marketing attribution so important anyway?  

“The reality is that marketing has become THE most efficient way to accelerate growth in our digital economy. The imperative is to connect the dots, so each marketing expense dollar is aligned and reported against revenue growth.”

- Paul Albright of Captora. 

A well-oiled marketing attribution system can result in efficiency gains of up to 30%. At its core, attribution modeling enables marketers to allocate resources in a strategic manner. Marketers can ensure that they’re actively driving conversions by optimizing their spending based on data-driven metrics. Zendesk’s marketing team, for example, can use a variety of attribution models to derive an understanding of what campaigns are working, and what campaigns aren’t. Accordingly, they can make evidence-based decisions on where to invest and what to alter. Ultimately, this results in a notable rise in ROI, a stronger grasp of SEO/SEM, and an improved alignment between marketing and sales. On average, marketers employ at least 6 communication channels to reach their customers today. As this number continues to rise, attribution will only become increasingly critical to the success of modern marketing initiatives. 

________

All that being said, marketing attribution isn’t without its challenges. In fact, even after the emergence of highly effective multi-touch models, several organizations continue to report attribution manually through spreadsheets. 

There are many considerations that go into choosing the right attribution model which can present several challenges for the marketer:

The Sales Cycle: 

Attribution is a lagging indicator. It takes time and patience to see if models are working. Based on the length of the sales cycle, the effects of a new campaign or changes made into existing ones will reflect much later into the future.

Ease of Set-up and Implementation: 

30% of companies in the UK say that they have chosen their current attribution model based on ease of use. If put in a position to choose between a model that is easy to implement and a complex model that would be tedious for the team to implement, marketing heads would prefer the simpler model. Similarly, technological limitations may also hinder the execution and implementation of attribution models. 

A Culture of Data and Measurement: 

To be able to value the insights provided by attribution models, there needs to be a culture of measurement and accuracy within marketing teams.

Communication of Insights: 

Communicating the insights from the model is significant for communicating cost justification as well as for taking action based on the insights from attribution. To get funds and approvals for software costs, and implementation costs in terms of time, effort, and training, the team needs to be able to communicate the insights well and accurately.

Attribution to Improve, Not Prove: 

Marketers often use attribution to prove that campaigns are working. As mentioned in the earlier section, this is important to be able to justify costs. However, limiting attribution to this purpose can lead to lost insights and higher costs. Attribution, at its core, is directional in nature. Attribution models can be used to see what is working well and also to check what is not working and needs to be abandoned. Marketing and Sales teams are often working on several kinds of campaigns and this is a useful tool to see which campaigns are performing better and can be emulated in future projects.

Volume bias: 

Most often, an organisation’s highest volume campaign can show up as its most successful campaign if marketers do not track other metrics like conversion rate and win rate. To understand, let’s consider the example of an organisation that sells CRM software to businesses. Say in the last six months, they saw a total of 500 downloads, out of which 400 were attributed to Campaign A which was implemented in the form of in-person promotional events like webinars while the remaining 100 were attributed to Campaign B which was implemented in the form of ads on YouTube and Instagram. By themselves, these numbers make it seem like Campaign A was the more successful campaign. But what if we find that the 400 downloads were made by customers from a total of 10,000 attendees in those in-person events while the remaining 100 from the second campaign were made by customers out of a total of 500 users who were presented with the ads. So if we look at the conversion rates for Campaigns A and B, we see that they were 4% and 20% respectively. This comparison could possibly give us the insight that if Campaign B was promoted further, with more funds and effort directed towards it, the organisation might’ve seen more downloads of its software with the it’s higher conversion rate relative to Campaign A.

Absence of predetermined hypotheses: 

To get effective insights from an attribution model, marketers need to be specific about what they’re trying to measure. For example, say the conversion rate for leads from campaign X within the period of the last 30 days since it went live for geographic location Y- can be used to understand if a campaign was successful within the target audience from that location. If marketers do not know what exactly they are looking for, they will end up giving an overall attribution report and miss out on gainful insights.

Invisible touchpoints: 

Several attribution models being used by organisations do not account for certain important touchpoints. Models that do not track the relationship between online activity and offline sales may lead to digital signal bias. For eg. one might have seen the ad for a clothing app on Instagram but they decide to go to the store and purchase the item. Models that do not include sales touches may not include the impact of sales actions. On one hand, it may hamper the accuracy of the outcome metrics and on the other, it may cause disarray with the sales teams instead of aiding collaboration between the two teams.

In order to choose the right attribution model for your team and reap the benefits that attribution brings to modern marketing, marketers need to be wary of these challenges and address them.

In further blog posts, we will be exploring the various challenges of attribution that we have outlined here in greater detail.