How To Measure the Impact of Your Brand Awareness Initiatives

And Get Your CFO Off Your Back for Good!

Photo by Pexel

The easiest way to explain away the ROI on marketing initiatives is to chuck them under brand awareness.

The assumption is that it cannot be directly measured even though its impact cannot be denied. So, for years, our cost-cutting finance partners have struggled with this concept, sparsely approving budgets for brand initiatives far between.

Take John, for example, who gets approval to run a brand awareness campaign on various digital channels for a mobile banking app. For performance reporting, he tracks metrics such as impressions, website traffic, social media engagement, sentiment score, share-of-voice, etc. The big question, however, remains — how does John report the impact of these interactions on a customer’s decision to download and use the mobile app?

Let us help John justify his investment by looking at three critical concepts:

1. Customer Purchase Journey
2. Marketing Attribution
3. Propensity Marketing

Customer’s Purchase Journey

I have listened to several customer journey experts oversimplify the purchase journey. A frequently used tool to explain the path to purchase is the sales funnel.

The idea of the sale funnel dates to 1898 when E. St. Elmo Lewis developed a purchase funnel — a marketing model which illustrates the theoretical customer journey from the moment of awareness to the actual purchase of a product or service. Is the tool still relevant today? That is a discussion for another day.

It is called a funnel because many potential customers may begin at the top of the sales process, but only a fraction make a purchase. In its simplified form, the stages a customer goes through using this model are:

1. Awareness

2. Interest

3. Desire

4. Action

You may read up on the sales funnel and its importance here.

The customer journey is not linear or this simple, however. A customer can have a hundred interactions with a brand on multiple touch points before making a purchase decision. It could make tracking customer interactions very complex.

Marketing Attribution

With big data comes the possibility of tracking customers' every digital interaction with the brand. Attribution modeling is a set of rules for assigning credit to the various touchpoints on the customer purchase path.

This model is one way John could better understand which customer interaction contributes more to the purchase decision — in this case, the download of the bank's mobile app — then pull more resources towards what works.

“Attribution modeling allows marketing campaigns to stop with the throwing spaghetti on the wall to see what sticks technique, work smarter not harder, and harness the power of return on investment (ROI) data.” — Brittney Sovik

Depending on the type of campaign you decide to run, you could choose to attribute more value to the first or last interaction, distribute evenly or progressively increase value from the first to the last interaction. You can watch a summary of the various attribution models in this video here.

It is worthy of note that attribution can apply to offline and online customer interactions.

Propensity Marketing

Going further down this path, is it possible to predict behavior, the likelihood that a customer would purchase or churn when exposed to our various marketing touchpoints? Yes. And this probability is assigned a score called the propensity score. The propensity score increases or decreases per visit as the customer progresses down the purchase path. Using machine learning, imagine if John could forecast which interaction would convert eventually. Or perhaps, which customer was most likely going to download the app?

By targeting customers who are most likely to convert, propensity marketing has the potential to reduce media spending, boost conversion rates and improve campaign ROI.

Final Notes

Now picture John confidently providing the attribution scores showing the impact every interaction contributed towards customer conversion. He also forecasts potential customer behavior on his next campaign spend — with a 75% accuracy.

Do you think this will have any impact on budget approvals? Will John’s initiatives be taken a bit more seriously? Will John be more efficient with his Advertising budget spend?

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