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Writer's pictureFahad H

Are you grateful for digital? Part 2: Q&A


In my most recent

column, I challenged you to ask if you were grateful for digital. I argued that while marketers claim to be customer-centric, our campaigns rely more on our need to meet sales goals than any objective of the customers.

Well, it got me thinking, do others have similar feelings? Are they grateful for digital? I asked Lynn Wunderman, a board member at PebblePost (my employer), how she feels. Wunderman is a seasoned marketing professional with over 30 years’ experience in direct marketing, database marketing, communications, consulting and general management. Turns out, she has some strong opinions herself, and she shared her insights below:

Q: Are you grateful for digital?

From a data perspective, I find it’s a mixed blessing, and as you touched on in your column, many of my colleagues feel the same way. I am grateful, because all the data we have access to today gives us the potential to make digital marketing really timely and relevant. However, I’m not grateful because there’s just so much data, and it can be difficult to access for supporting meaningful analysis.

We’re literally drowning in data, but starved for knowledge, to paraphrase John Naisbitt. All this data is both a blessing and a curse because making it actionable is such a tremendous challenge.

Q: Customer-centric? Or transaction-centric?

As marketers, we want to be customer-centric — it’s always been our goal. The problem is we’re simply too transactional. We’re often not looking at the bigger picture.

To give you an example, a marketer may use GPS data to determine that a person is near a quick-serve restaurant. Based on that data, the consumer is served an ad featuring an offer for that QSR. Sounds like a smart strategy, right? It is on the surface, but the marketer may have no idea what the potential value of that consumer is. They may be a high-value customer, or they could simply be someone who only visits when they have a deal for a cheap meal — and, in reality, is highly unlikely to ever set foot in that restaurant again without a bribe.

So, that’s not really customer-centric. It’s convenient, I suppose — and opportunistic — but proxies will only get you so far in building a long-term, profitable customer relationship.

The roadblock along our route to customer-centricity is that our approach is not holistic. As marketers, we’re simply not structuring the data in a way that allows us to see the patterns — patterns that could give us the insights we need to market more successfully.

Many veterans of our trade will find this oversight frustrating because in traditional direct marketing, we typically created segments based on the value of our customers. RFM data (recency, frequency and monetary value) was used, and looking back, it may seem rudimentary, but it was effective — largely because it normalized and summarized transactional information across all customers, thus allowing predictive patterns to emerge.

Even in the absence of transactional data, we would use proxies (like scanner panel and syndicated data) to understand and predict who our high-value customers were and where they were in their life cycles. We knew who was worth investing in, and we could avoid attrition by understanding the potential long-term impact of trigger events and making offers that were relevant to where they were in their customer life cycle.

Marketers today have all kinds of data at their fingertips, but they don’t often have or use the tools to harmonize it all and organize it this clearly.

Ultimately, we’re just not being sophisticated enough in our approach to data. We’re limiting our perspective to offers that are specific to what’s happening now, rather than looking at the big picture. We’re grabbing for that low-hanging fruit, and it’s critical to return to that full life cycle view, and the customer’s relationship with the merchant or marketer.

Q: Can we find a way out of the black box?

The tools we use are partly to blame. Black-box programmatic tools and DMPs (data management platforms) are great for predicting the next click, but you lose some nuance along the way. Older tools gave us the opportunity to interpret that data and gain a deeper understanding of segments and audiences. Most platforms and algorithms don’t allow for the learning that helps us understand what entices consumers to inch further along the path to purchase — only that they are moving down the path.

Not knowing that “why” can really stymie the creative process because we lose some understanding of who our audience is. To really be specific in our messaging and build real conversations with these people, we need to understand not just who they are in data points, but what distinguishes them from the broader universe. In other words, it’s not what they have in common with other shoppers that’s important; it’s what’s different about them.

That’s what’s predictive and what moves people up in terms of targeting potential. If you have that information, it feeds the creative process.

And that’s another critical point in this data conundrum: Creative now stands in the shadow of data, when really the two need to share the spotlight. Data can’t do all the heavy lifting in marketing, and marketers must recognize that and invite creative back to the table.

We can use all the data in the world to understand exactly who our target customer is and why they’re there, but we need to bring creative into the process so that we can actually engage them. The art of understanding the customer and how to talk to them seems to have vanished, and in a world where attention spans and digital canvases are getting smaller and smaller, that art is more important than ever.

In conclusion

So, given her perspective shared above, Wunderman’s point is this: Data is important, but it’s not everything — certainly not the way we’re currently using it today. She’s calling for marketers to stop focusing on individual transactions and start focusing more on individuals and what it takes to build long-term relationships and brand advocates.

Maybe if we stop focusing purely on the science of data and spend more time on the art behind the interpretation of data and how it fuels the creative process, we can all start feeling a little bit more grateful for data, and ultimately digital, too.

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