Too many marketers have been fooled into thinking that winning at big data will solve all their problems. Actually it’s more complex than that, says Frankly Partners chief digital officer Roope Ruotsalainen.
If marketers and agencies talk of anything, it’s big data. Such conversations have led them to believe that data alone will drive their businesses forward.
The truth is that while data has enabled brilliant solutions through automation and algorithms, too much hype has created a false sense of reality. Big data has become the master of marketing thinking.
This attitude has created a serious risk of big data myopia. The problem is that businesses increasingly assuming that “big data solves all problems”.
To understand how this can happen we need to consider the two types of saved and collectable data value points: real-time data and cumulated historical data.
The former helps advertisers to target in real time or helps call-centres to address customers’ problems better. This is applied to micro-optimisation of specific channel issues but it doesn’t solve the major business problems.
The second type of data value point is historical data. It might explain how customers are behaving, but it doesn’t explain why. Nor it doesn’t tell us anything about potential customers.
As companies invest billions in big data, their leaders start to thinking, “We’ve invested on big data solutions, so we already know our customers.”
The problem is that, while companies only optimise micro issues, they end up with great detail but a limited vision of their customers.
For most brands micro-optimisation already takes place with each digital marketing silo optimised. What fails to happen is the necessary management of the interaction between marketing communications, distribution, pricing and product development.
What brands need is strong, actionable customer insights that will lead business and brand strategy
What brands need is strong, actionable customer insights that will lead business and brand strategy. What they should understand is “what customers are aiming to get done”, whereas what the data tells them is what customers ended up doing.
With the right insights they could plan their value creation to support the real customer needs. Big data alone will not deliver this.
The truth of this analysis is clear from one company we have been working with. They are a huge ecommerce business with incredible in-house resources and skills in areas such as digital marketing, web and CRM analytics, and ecom/web development.
They probably have better in-house skills than many good agencies and that’s often the case in sectors such as betting, travel and online retail.
Our client has a data-driven culture and teams of analysts, as well as a sophisticated internal “digital sales department” to optimise their massive visitor flow and maximise the revenue. They have moved beyond personalisation engines and use machine-learning methods for optimising.
Despite all this expertise, however, the company has a major issue when it comes to big data: they are optimising everything in silos.
That means that marketing managers aim to maximise the revenue of a single product they are responsible for, while the digital sales department aims to maximise the revenue of each session, for example.
Serious macro challenges
This micro approach creates some serious macro challenges: potential revenue growth is driven by cross-selling products across business units. As they have been optimising user flow to maximise each session revenue, they ended up boosting products that lead to quick returns, but high churn in the long term, thus lower customer life-time value.
The analysts recognise this issue, but their challenge has become organisational. Everyone understands the importance of the macro level optimisation but their business unit, team, and personal goals (and work descriptions) don’t support that aim. The result is that managers, unit directors, unit and channel specific analysts say one thing, but end up behaving differently.
The bottom line is that a big data approach can lead to even highly sophisticated companies optimising the wrong thing.
Our solution for this client has been to deliver a cultural change programme designed to identify which kind of issues could be show-stoppers and ensure that all relevant employees from the C-level to grassroots to understand, why in this case, lifetime value should be the tool they optimise.
This has to be applied not just in principle but developing an understanding of what that means in practice for really different roles.
The reality is that by positioning big data as the answer to every question, we miss the fact that it doesn’t tell us what consumers want to do. It can create corporate structures that encourage everyone to do the wrong thing.
Big data is part of the solution to our marketing challenges but only where applied in conjunction with great insight that may or may not stem from that data.