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The Phases of Marketing Analytics Maturity

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Marketing Data Stages w Exec Buy In

According to a Fournaise Group study, a staggering 80% of CEOs don’t trust their CMO. By comparison, 90% of those same CEOs trust their CIOs and CFOs.

The Fournaise study is still being actively quoted by reputable sources today because it resonates with the underlying problems business leaders identify with their marketing leaders today. Let’s break down the Fournaise results to get some insight into why CEOs think CMOs aren’t succeeding:

  • 71% of CEOs feel that B2B CMOs are too invested in the next new technology that will supposedly boost lead generation
  • 75% of CEOs think that CMOs misuse (and don't understand) the words "Results," "ROI," and "Performance," and they don't speak the same language as the rest of the C-Suite
  • 85% of CEOs want B2B CMOs to focus on KPIs like Prospect Volume, Prospect Quality Rate, Marketing Effectiveness Rate, and Revenue Potential generated by marketing
It’s no coincidence that the Harvard Business Review published that CMOs have the lowest tenure of all executive positions (50% of the average CEO).

As marketers, we understand that there's more nuance to marketing performance than in other business areas. Awareness activities like press, paid search, and SEO work are difficult to directly correlate to revenue. However, it's not as difficult as most of us make it to prove marketing's value. We have the data. And with the right priorities, tools, and skillsets, we have the means.

Phase 01: Ad Hoc

Marketing Data Phase 1

The Reality

Early (hopefully) in a company’s development, the leadership team understands they need marketing to get the word out about their company and product. After the initial headcount is approved and the costs start to pile up, the leadership team starts asking for proof that the marketing activities are working.

There are several problems with this scenario:
  • A small budget means the cheapest tools are used
  • Cheap tools mean a lack of integration
  • A lack of integration means a lack of data structure
  • Lack of data structure means reporting is painful if not impossible


Unfortunately, none of these things contribute to a particularly successful picture of a leader.

The Bandaids

If the company is small enough, the VP of Marketing may pull together stats from different sources. Because the campaign data isn't integrated with Salesforce, it's impossible to definitively say how many leads marketing was responsible for. They can measure:
  • Social Media followers, likes, shares, and comments
  • Website sessions, bounce rate, form fills
  • New names acquired


And that’s about it.

The C-Suite isn't impressed because when the marketing leader is asked about profitability, marketing efficiency, and prospect growth, they get a song and dance about awareness, "directionally accurate," website visits, and form fills. Marketing doesn't have the people or tools necessary to tie their activity to pipeline in a meaningful way.

Even if they hire someone good with numbers, an investment in better tools is necessary. Google Sheets Connector and Excel Connector will only get you so far.

The Fix

If you want to tie marketing activity to pipeline and revenue, you must purchase tools that inherently integrate or purchase integrators and then normalize the data to make it usable. This is also when you should start using the Campaign and Campaign Member objects in Salesforce and putting some rigor around recording budget and actual expense data for these campaigns.

If you need to make the most out of a limited budget, get a marketing automation platform (MAP) that integrates with your CRM. Find someone who can set up the proper tracking on your website. And do your best to find marketers who understand the necessity of using analytics to prove a return on investment.

Phase 02: Descriptive

Marketing Data Phase 2

The Reality

The descriptive phase gets us to the point where:
  • Forms are integrated with the MAP
  • The MAP speaks to the CRM
  • Standard campaign and campaign member objects are used in your CRM
  • Enrichment tools have been purchased to expand on limited form data collection

Because a campaign member is being created each time someone interacts with marketing (instead of just recording how a new name is acquired), it’s possible to rig something that automatically associates a campaign with a new opportunity. This may also mean you have the sophistication to record lead stages and measure lead generation stats like MQL, SQL, and so on. Whether or not this is the case is entirely dependent on whether or not you hired someone with the ability to automate this process correctly.

At this point, we're capable of source reporting. To a degree. But it's difficult to say where any deal comes from. Truthfully, each deal is a team effort from sales, marketing, and your channel team (if you have one). This means that each team will likely report a different team contribution number to the board or, at the very least, sit in a quarterly meeting arguing about who gets "credit" for bringing in a given sale.

Marketing is still feeling a lot of pressure to prove that their awareness-building works. People aren't satisfied with an overall uptick in web visits, social followers, and inbound leads (especially when those inbound leads are all attributed to a chat tool and not the channel that got them to the home page in the first place).

The Bandaids

I’ve seen a wide array of manual checks put in place to keep Source reporting going with the least amount of infighting possible.
Pro Tip: There’s still infighting. It just usually doesn’t happen at the board meeting.

"Fixes" include sales ops confirming the source at the time of opportunity close. A deal review each month held by stakeholders who do their own research on each opportunity ahead of time. My favorite is the acceptance that this is a “directionally accurate” metric, which only works if the measurement isn’t part of someone’s compensation plan.

The Fix

If you want to start proving the value of early funnel activities, you’ll need to invest in attribution technology and an analyst who is gifted at explaining the value of attribution to the C-Suite. They need to prove why marketing needs attribution, why it’s useful, and why they use the models they do without:
  • Boring the CEO
  • Triggering the CFO
  • Offending the Sales VP

For more on selling attribution to your executive team, check out our article here.


Added bonus to this phase: source data is less critical to proving marketing’s value, which means arguing about who sourced an opportunity because a thing of the past.

Phase 03: Informative

Marketing Data Stages (3)The Reality

A few things happen before the Informative phase can really kick-off. The most notable is an urgent need to put data hygiene processes in place and a rush to get campaign hierarchies and naming conventions in place.

Data hygiene becomes an issue because marketing has been purchasing contact information, enriching data from multiple sources, and blowing up duplications because they use the lead and contact objects. The humans inputting data haven’t been helping, but their damage is usually done on a smaller scale.

Depending on the attribution tool you purchase, you may also walk away with a long list of things you need to fix before the tool can be implemented. This may mean backfilling old data, putting campaign hierarchies in place, and switching custom channels and naming over to a more standard naming convention.

Some tools do all of this for you ::cough:: CaliberMind ::cough::.

The big benefit of this stage--if you achieve executive buy-in--is that you now have the means to prove your campaigns' value. Even the early funnel campaigns.

The Bandaids

You could try using your MAP’s attribution and customer lifecycle tracking, but I’ll warn you that it won’t be pretty. First of all, most of these platforms don’t have a standard object for opportunities, so connecting the dots is dicey. Secondly, some of them are still single-touch attribution or remakes of the demand generation funnel.

The same goes with Salesforce Marketing Cloud.

With either option, your results will be entirely dependent on:
  • How well structured your campaigns are
  • How consistent your data entry was
  • How clean your account data is
  • Whether you’ve dropped the lead object

The Fix

Invest in a tool that can connect to all of your data sources. If you purchase something that only plugs into your CRM or MAP, you're limiting the breadth of data considered, which means you do not see the big picture.

Think of the channels you struggle with proving value today. If your attribution tool doesn't address these areas, what's the point of going through a lengthy exercise trying to clean the data you can already get a read on?

Find an attribution company that will partner with you on best practices and does a lot of the data work for you. Don't settle for being left out to dry when it comes time to get your data into shape.

If someone tells you that they don’t need to fix your data to give you results, run away. Remember the data analysts credo:
Garbage in. Garbage out.

Phase 04: Real-Time

Marketing Data Stages (4)

The Reality

Now that we can measure different stages in the buyer journey and prove the value of early funnel campaigns, the focus turns to optimizing the marketing to sales hand-off. We recognize there’s a disconnect between the teams. Marketing doesn’t understand why sales doesn’t follow up on their leads, and sales thinks all leads are essentially garbage.

This stalemate eventually leads to change. Marketing must become more sophisticated about calculating the ideal customer profile, measuring engagement, and learning to prioritize

The Bandaids

You can try using sales’ definition of ICP or you can start looking at engagement scores, closed deals, and demographic stats. If your systems aren’t integrated, you’re going to have a lot of CSV files and spreadsheets on your hands.

The Fix

The only way to stomp on the “all leads are garbage” argument is to have a system that can look at accounts and leads multi-dimensionally. You should be able to look at successful deals and look at account and contact data related to those deals. Then compare it with unsuccessful leads to identify whether your data is meaningful.

Or buy a tool that does all of this for you and layers on machine learning models. As long as you can build an engagement model that factors in ICP and sales sees success and buys into your information, you have a winning combination.

Phase 05: Predictive

Marketing Data Stages (5)

The Reality

With reliable performance data comes the ability to forecast whether or not you’ll hit your goals. If you’re fancy and incorporate machine learning into the mix, you can even map the ideal buyer journey and start really personalizing content by vertical and persona.

You’re starting to leverage intent data, but there are so many indicators to choose from that it’s not operationalized yet. You know that if you flip a switch and give access to sales, they’ll start running after every lead and throw the ICP and Engagement scoring models you’ve built (and finally agreed on) out the window.

You have integrated your ad platforms and can finally speak to ROI, not only of your trade shows, events, webinars, and lead form fills but even your digital advertising. You can even bring in the cost of your personnel and total budget to look at customer acquisition cost and start making adjustments to positively impact this ratio.

The rest of the C-Suite no longer argues with you over your data, and you’re prepared to speak to anomalies with an action plan.

The Bandaids

Wading through intent data is a little bit like trying to drink water out of a fire hose. There can be petabytes worth of data, but only a fraction is meaningful. Dumping the information into a data lake or warehouse can get messy fast.

The Fix

When it comes to intent, your options are limited. Using machine learning to cut through the noise and identify meaningful interactions is the only way to whittle down the data to the point it’s useful enough to pass on to sales (or the rest of the business). Once the recipe is dialed in, we’ve seen customers shorten their sales cycle by 4-6 weeks.

It’s one thing to have tools that spit out KPIs. It’s another thing altogether to have an analyst who can dig into why trends and anomalies happen and serve up an action plan to address the issues. Invest in a talented data analyst (or two) to stay on top of your data so you can spend less time answering questions and more time providing strategic value to the business.

Phase 06: Prescriptive

Marketing Data Stages (6)


This is a CMO’s utopia.

Not only do you have the answers to marketing's problems, but you also have insights that can help the entire go-to-market strategy. Because you've proven your department's contribution and efficiency, you're now viewed as a strategic business leader.

You've attained the status of a visionary leader, which only 17% of marketers can claim.

Congrats! The sky’s the limit.

A Few Nuances Worth Mentioning

Marketing Data Stages w Exec Buy In (2)

Ad hoc, descriptive, and informative phases are often a response to the executive team or board members demanding proof that marketing is positively impacting the business.

Real-time and predictive phases typically begin a new line of questioning from the rest of the leadership team. The focus is no longer on whether you know if what you are doing is having any impact. They now want to know if you can maximize your impact without continually asking for more budget.

The prescriptive phase marks the end of people questioning whether marketing is pulling its weight and can scale with the business. If you have the right tools and resources, you have the information needed to make you a strategic leader.
Marketing Data Stages w Tech

As a part of our "Bandaids," we mentioned that you could purchase tools to move along in maturity. You can buy integration connectors, visualization tools, and piecemeal solutions. Or you can work with a B2B marketing platform that is as innovative as you are.

We wish you the best on your data journey!

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