Marketing Decision Making Has Never Been Harder

Many marketers, and those who determine marketing budgets, would hand-on-heart say Mr Wanamaker can rest easy knowing his wildest dreams have come true. The inherently measurable nature of digital means we finally have everything we need to accurately determine wasted ad spend and more.

Except, unfortunately, I don’t think we do.

Sure, in lots of tactical areas of marketing, data is rightly the final decision-maker. There are great data decisions made every minute of the day. These decisions are made behind the scenes by algorithms and AI, as well as by marketers at every level. 

This is, however, far from the full story. Many of the decisions we make with data are simply not right, or they narrow our marketing horizons in major ways. Given where things are heading with more complex buyer journeys, growing numbers of ad platforms and increased online privacy, marketers and decision-makers need to better understand data do’s and dont’s if they want to stay ahead of the competition.

You don’t need to be a sophisticated sports fan to understand there is no single KPI that allows you to easily compare the performance of every player in a sports team. Points scored might be a great KPI for attacking players (sometimes), but a very poor KPI for the equally important defenders. 

And yet, it’s all too common for marketers to weigh up the value of all campaigns using a single KPI like Cost Per Lead (CPL) or Return On Ad Spend (ROAS). At a simple level, it makes sense. The ultimate goal of your marketing campaign might be to generate leads, so let’s find those campaigns or activities that generate the lowest CPL’s and double down on them.

Here’s a simple example. A budget-restricted marketer is running a bottom-of-funnel Google Ads campaign at the same time as a top-of-funnel Facebook Ads campaign. GA4 shows that the CPL from Facebook is a whopping 10x higher than Google Ads. It’s an easy decision to shift the entire budget to Google Ads.

If only marketing was so simple. Here’s an example from a recent client campaign here at Rocket.

In the April to June period you can see that the spend in Facebook dropped by roughly 15%. At the same time, the conversion rate in paid search dropped by an even larger amount. 

The ROI from Facebook was lower than Google Ads, hence the reduction in budget. But as you can see, a deeper look into the data uncovers (in hindsight) that Facebook Ads performed a meaningful, but initially hard-to-measure role of boosting the performance of the Google Ads campaigns. Splitting budget between both platforms was the smart play.

We see this type of impact time and again. Campaigns do not exist in isolation from each other, because they often form part of the same buyer journey.

Without changing ad spend in Facebook and looking specifically for this correlation, it would have been very tough to spot this near real-time impact on search conversion rates. And this is still a very simple example of one change triggering something very measurable, very quickly.

What about the very real scenario of your marketing strategy involving a number of different activities, where CPL or ROAS is not going to tell the full story, as the activities are designed to fill your funnel rather than drive direct sales or leads? Let’s say at the same time as the above example, you were also running YouTube prospecting ads, promoting a webinar, driving traffic to a piece of content and had a stand at a major in-person event.

How do you even begin to use data to figure out which of these activities ultimately best supported an overall lift in sales or leads?

To add another level of complexity, let’s say your buyer journey is longer than a few days or weeks, and the sale itself happens offline and is not, therefore, readily tied back to anonymous data in GA4. We regularly work with clients where the buyer journey is a few touchpoints over a few days, but we also regularly work with clients where the buyer journey is dozens of touchpoints over many months or even years.

In the scenario where you kick off a new marketing activity, but most prospects won’t be speaking to you or buying something for many months (or even years), how can anything in Google Analytics tell you how valuable that specific activity has been? And will you, as a marketer, have the courage and patience to believe in the activity while it simmers away in the background? 

Finally, how about the reality that it’s getting harder, not easier, to track people online? Privacy changes have significantly reduced the reliability of marketing data, and this is only going to get harder as time goes on. When the data for even simple activities is no longer as reliable as it once was, what are the dangers of relying on it too heavily when it comes to real-world complexity?

If the only tool you have is a hammer, you tend to see every problem as a nail. It’s the same with data and marketing. If, in the spirit of reducing uncertainty, GA4 has become your decision-making tool, then everything starts to look like a data problem.

We live in a very complex world. Search, social, display, out-of-home, podcasts, webinars, YouTube, TV, radio, print, reviews, word of mouth, and so much more influence our decisions. 

Don’t believe me? Note down the last 5 things you purchased for the first time (or are considering purchasing), and think about how you first heard of them and the subsequent actions you took before making a purchase. Good luck with accurate recall for your own buyer journeys, let alone understanding other people's unique and complex journeys for the same products.

When it comes to your example journeys, I’m going to guess that only some of your touchpoints would have appeared in GA4. Even then, I’m going to assume different KPIs would have been needed to assess the effectiveness of these different activities. 

If the marketer controlling each campaign had made the decision to make all their decisions using data, and they had gone with a simplistic model of using CPL or ROAS to judge each activity against the others, would you still have ended up a customer if various tough or impossible to measure top and middle of funnel activities had been dropped in favour of high performing bottom of funnel activities?

Firstly, you don’t throw out tools like GA4. Used correctly, they are invaluable. However, you must be clear on which marketing activities you can measure in GA4 versus those you simply cannot. And you need to be comfortable with the difference.

For those activities you can measure, what’s the right metric to give you a true insight? ROAS, CPA, CPL, visits, email addresses collected, downloads or something else? Every measurable activity deserves its own best-fit metric(s). 

And in addition to the metric, and just as importantly, what’s a realistic timeframe for an impact to be felt? How long should you give a measurable activity before you use data to decide it’s not working?

You need to also consider activities that may not be measurable on their own but have an important supporting impact on activities further down the funnel. For example, are prospecting ads improving the performance of your search campaigns?

But here’s the hardest thing for many marketers; in this era of data saturation, there are going to be times when you have to use your gut rather than data to decide if a particular activity is worthwhile. 

Are you in tune with your audience and their buyer journey enough to make the call that, with or without data, you’re sticking with a particular activity because you know it makes sense and delivers value to the right people at the right time? Most great marketing strategies will feature such activities, and they will reap the rewards for their insight and courage.