- Strategic consulting
We rely on data to make important decisions – from harnessing the power of big data, to running small-scale growth marketing experiments – the list is endless.
One thing is for sure, there’s no escaping the fact that we use those data-driven insights on a day to day basis, but can we be sure those insights are dependable?
Are your insights being served on a plate of self-interest?
I’ve recently been growth consulting at a large UK retailer. Having worked closely with the CEO and CMO, it strikes me that they are facing real challenges when it comes to the insights presented by internal and external teams.
Often insights - which are used as a tool to unlock growth - are a product of small-scale experiments. And while they can be effective, the hypothesis, tests and resulting conclusions need to be approached scientifically. Measurement needs to be accurate and statistically significant.
I’ve seen success attributed to small data sets and conclusions made where there’s no clear evidence. Yet the insights are promoted at a senior level and potentially expensive investments are made on the back of them.
I’ve also witnessed situations where suppliers have presented insights that determine how large sums of marketing investment are made with them. Many media agencies still work on a percent of media spend model, and with attribution being a complex subject, it’s easy for internal teams to be bamboozled or shown only part of the picture.
Self-interest can be seen in the confusing way that Facebook attributes conversion. When Facebook shows an ad or gets a click on and let’s say the customer conversion happens 20 days later, Facebook attributes the day one click as a conversion, which if you’re using Google Analytics would not accurately reflect the attribution model.
Do you have the right people
Digital transformation has seen brands challenge their legacy digital and marketing team structures. It’s essential that there is an independent person or team involved early in validating data measurement techniques and concluding insights that are then communicated.
It’s also essential that brands foster teams with strong data management, data science, and analytics capabilities. I’m not alone in this belief, with research from Forrester stating that 74 percent of companies consider data science among their most important initiatives.
But despite the consensus that it’s important to recruit talent with this expertise, a recent survey by Adobe reported that for almost half of senior decision makers, a lack of internal capabilities or talent in data analysis was the biggest barrier preventing them from drawing actionable insights.
I’d like to see marketing teams incorporating a top-down performance-led, metrics-focused approach to everything they do, balancing the art and science of marketing.
Can you rely on your marketing technology?
Digital transformation is more than just people. It should be an ever-present constant that enhances the marketing role. Technology plays a key role in understanding consumer behaviour.
As stated within the Adobe Research 2018 ‘context is everything’ report: "Brands need to be analysing the entirety of their customer data. They should be taking advantage of technologies such as AI to dig deeper and unearth relationships, context, and insights within that data.”
Big ticket martech investments are expensive and take time to implement and see the benefits. But it is possible to achieve a lot without spending vast sums of money - Google Analytics offers an excellent free start point.
Data-centric culture starts at the top
Using data, we can understand consumer behaviours and audience responses to all marketing activities across multiple channels. This ultimately provides huge levers for wider, rapid business growth. But in order to make the most of this data, a spirit of adventure and curiosity needs to be fostered from the top.
John Veichmanis, CMO of online retailer Farfetch, has enjoyed a hyper-growth success story using data. He explains:
When I joined Farfetch in 2015, my first hire was a data scientist. We now run around 1000 growth experiments every year and only one in every ten produces a positive result. Embracing the idea that nine out of every ten things we try don’t work is key. This starts with the buy-in of our CEO who has been hugely supportive and acknowledges that growth comes from those experiments that do work”.
Data doesn’t have all the answers
I’m going to conclude on a cautionary note. Data doesn’t have all the answers. As stated by Shama Hyder, Founder and CEO, Zen Media: “Data is only as good as the questions it answers and the meaning we assign to it.”
It’s key to strike a balance between an over-reliance on data insights for decision making and the more traditional growth mechanics of innovation and creativity. After all, data cannot replace human intuition and it certainly doesn't remove risk from the growth equation. Think on.
How are you using data to support business growth?
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This article was first published on Forbes: