I am on summer break back in London and caught up with an old friend over at the British Grand Prix in Silverstone. He is an aerospace engineer, and before the race was talking about new developments in engines, and parallels in what he does with the technology at use in the race.
I thought that F1 racing has similarities with modern marketing. There is a massive amount of data crunching, before, during and after a race. The data is incomplete because racing teams don’t know the specifics of setups and performance telematics of their competitors’ cars. You do know generally how well you are racing and competing against yourself to improve performance in key areas.
Similarly, marketers have to be increasingly more precise in a constantly changing environment, and with a partial picture of their customers. They also have to contend with competing narratives by other marketers vying for the customers’ attention, and finishing ahead of their competitors.
Big data platforms can help close this gap. Let’s look at a couple of ways investing in in one can drive increased effectiveness and efficiency.
Without a focus on key objectives, every new piece of data will look attractive and every additional bit of information will look important. The focus shifts on these objects rather than the objective. The effort becomes a whack a mole type frenzy of activity. To start, objectives have to be specific, scientific, scalable, and measurable in the short term. Some sample objectives include: increase response rates for mobile campaigns, predict future purchase, and reduce service issues
Just like in the formula one teams, there has to be a balanced team with the right skillset to understand the data in context to optimize performance and avoid blind spots. Using all the data to focus on engine performance but ignoring tire performance and wear will create a big blind spot for the team.
A balanced team comprised of data scientists, the marketing communications experts, the marketing technology and advertising specialists, and strategists are critical, because a misaligned team is not going to be able to have the broader view into performance and impact necessary to react quickly to changes, needs, and requirements.
Expand, Enhance and Enrich
All the new data sources and views must align to offer more actionable intelligence. To do this marketing teams must assess what information is currently available, and what additional information would be useful, if not critical to the desired outcome. It can be new information providing something previously unknown like product usage patterns, or information which adds to existing information e.g. better insight into share of wallet for the product category. The key is to focus on the right areas, and the data that will drive insights.
The limitations come in various forms, and they have to be anticipated. In my experience these have included coverage, actionability, stability and reliability of data. Overlap analysis to determine added utility, and a look back to assess the variability and stability of data are key. Another limitation is how the data can be used. There are industry guidelines as well as vendor and partner limitations on data used for campaigns, as well as measurement. These must be identified upfront.
Pilot with new capabilities:
To see the impact of the new capabilities and insights, there have to be test programs developed, launched and evaluated. These should focus on test and measure by parallel testing, measuring lift, then fine tuning and refining over a defined period of time.
On the trip back from the race, we continued the discussion and as I talked about the marketing space and what I do, I ended with a wink and a statement “but its not quite rocket science” to which he just smiled and responded “better you than me, rocket science seems simpler since it deals with the rational and physical while you have to contend with human factors like emotions and impulses. I don’t do that”
Marketers, start your engines.