Too much data, too few skills. To achieve personalization, there is another way

Solderthe provider of customer engagement software platforms, recently released their third yearbook Global Customer Engagement Assessment. The study, which surveyed 1,500 marketing executives in 14 markets, aimed to uncover the most common trends in customer engagement over the past year. At the topline level, they found that while customer acquisition costs have skyrocketed, value-conscious consumers are faced with more choices than ever in a volatile environment.

As a result, many companies are focused and invested in defending their base.

Specifically, their research found that:

• The number of companies investing most of their marketing budget in customer retention has increased by 36% compared to last year,
• Nearly all (99%) marketers report that they will shift their customer engagement messaging to prioritize personalized, human messages to engage with their customers in a more meaningful way.
• As a result, 53% report that they will send more messages with helpful advice, 49% that they will target customers based on financial metrics (e.g. household income), and 37% plan to send fewer promotions and commercial offers .

No wonder, given the environment in which we find ourselves.

What came as a surprise, however, were the findings surrounding the two biggest problems marketers face. Specifically, the research found that the two biggest problems marketers face are too much data and gaps in data analytics and management capabilities, where:

• 80% of companies say they collect too much data, leaving information available they can’t use effectively, and
• 42% of marketers said the biggest data management challenge is working with internal data scientists/BI teams who don’t understand marketing priorities, while 38% cited a lack of data skills among marketing talent.

The reason these findings are surprising is that these issues are known and trusted issues and have been around for a number of years.

For example, in May 2017 on a episode of my podcastJascha Kaykas-Wolff, who was Chief Marketing Officer at Mozilla at the time and is now chairman of Lytica, believed that marketers were getting lazy and collecting more data than they knew what to do with. This prompted Mozilla’s team to come up with the idea of Lean Data Practiceswhich is a framework to help them (and other interested companies) think about the decisions they make about data, focus only on the data they need, build appropriate security around that data, and engage users to help them help them understand how their data is being used .

In addition, inside another podcastthis time in July 2016, I spoke with Vivek Jetley, then Senior Vice President and co-Head of Analytics and Head of Corporate Strategy at EXL and is now Executive Vice President and Head of Analytics there. In that interview, Jetley highlighted that one of the biggest challenges companies face is a lack of “data” skills. He then broke this skill gap down into 3 broad buckets:

1. Data scientists – people who can do advanced analytical and statistical work. At the time, Jetley estimated that the skills gap for data scientists in the US and UK was around 3-400,000 people.
2. The bigger gap lies with the managers – those with the right amount of training and insight who can take the product of the data scientist’s work, interpret it, and decide how to use it. Vivek estimated that this gap is 3-4 times the gap for data scientists.
3. The final gap is with people who understand consumer behaviors and processes or have a Six-Sigma-like background, who can help manage the implementation of data insights across the various customer channels. Vivek estimated this gap at another 2-300,000.

Jetley further emphasized that this problem worsens when you move away from major urban centers such as New York, LA, London etc.

That was in 2016, and it can be argued that this location challenge has eased, given the advancement of cloud-based applications and the widespread adoption of remote working in recent years.

However, given the persistence of these issues, I arranged to meet with Myles Kleeger, President & Chief Commercial Officer at Braze, to get his thoughts on the research and what companies should be doing to address these challenges.

According to Kleeger, one of the main reasons behind the ongoing data and skills challenges is that “too many companies are focused on collecting as much customer data as possible without first defining a strategy for how they want to use it. New innovations in the fields of machine learning and generative AI will of course drive even more data collection by brands, which will only exacerbate this problem.While there will undoubtedly be compelling use cases inspired and enabled by these massive datasets and new capabilities, this does not change anything to the fact that you first need a strategy to use the data before you collect it, what else is the point?”

Kleeger continued that too much data exacerbates the skills gap, and instead of relying on behavioral data analytics or ML/AI techniques to drive better engagement and personalization, some leading brands are going “old school” and simply asking their customers what they want and where they are interested in.

This kind of approach is music to my ears and something I have long advocated for.

But what does that mean in practice? Well, for a brand like HBO max to promote the “Fantastic Beasts” movies, the company developed a tailored “What’s Your Hogwarts House” survey based on viewer preferences and history. The responses formed the basis for a personalized messaging campaign with more information about each customer’s house choice, as well as a hero image with their name embedded in their house crest. The approach ultimately resulted in a 3.36% increase in viewership of featured featured titles, a 3.12% increase in session launches, and a 6X increase in click-through rate associated with the in-app message.

In addition, the corporate wellness platform gym pass took a similar approach, using surveys to capture data about users’ interests, habits, and behaviors. This helped them personalize their posts based on their user interests, and that campaign resulted in 25% new net revenue and a tripling of signups.

The bottom line: These examples show that there is another way to achieve true and meaningful personalization.

It’s not just about collecting more and more data and then figuring out what to do with it. It’s about having the right strategy first, then gathering the right data (and that includes asking your customers) to help make that strategy happen. Doing things this way can help overcome some of the skill gaps brands face.

We hope brands pay attention and more and more people choose to avoid the vortex more is better.