It is a common, global problem in the digital age – how do you convert vast amounts of data into demonstrable business value? Marketers aren’t exempt from this conundrum, and the pressure is always on to justify the worth of running a marketing campaign in real world, practical terms.
So how can you glean the most profitability from a campaign? Start by addressing a core challenge: Separating the important data from the not so important.
More particularly, focus on demographic information that is easily accessible like age, gender, location. Then follow up by looking a bit deeper and adding data such as marital status and income. Grant Fleming, CEO of Leadify offers this advice to entrepreneurs and marketers.
1. System essentials
Beyond this, while choosing the right data is key, it’s wise to use the best direct marketing system possible for your marketing needs. For starters, it should report on the data that is most important. It should also offer smart dashboards that displays comprehensive information. And it should accommodate users who want to put analytics and insights together manually.
Related:POPI Proof Your Direct Marketing
Having all three in place – pulling together data, running analytics and translating those into presentable reports – is not just a nice to have. It’s increasingly essential, as direct marketing is fast becoming a saturated space. Figuring out ways to better personalise data, and target and curate the right audience for the right message at the right time has become mission critical.
2. Aid from the machines
The good news is that machine learning is set to take much of the onerous work out of personalising data. But the caveat is that its usagedoesn’t exempt youfrom being involved, as machines still need to be taught what constitutes good data to begin with. You thus need to know and understand how to curate data properly from the outset.
For the foreseeable future, you still need to understand what you are feeding the machine learning algorithms with, and most importantly, testing assumptions. Avoid the tendency to assume that because the results came from a machine, they are correct. Rather, conclusions drawn need to be continually tested, verified and honed where appropriate.
3. Pitfalls and challenges
But, while you may have a basis from which to extract more value from your data, what is preventing you? Among key obstacles that many marketing companies do not realise, is the power of the tools that are available to them, especially those locally produced.
This is to their detriment, as the tools readily available in South Africa boast sophisticated, yet simple, insight dashboards and reporting metrics that could power-up their marketing efforts.
As for a potential opportunity, this too is a topic that is often mentioned in other industries, that of creating greater integration with a variety of tools. In reality, few companies have managed to integrate their digital, social and direct marketing approaches well.
Getting more money out of your data boils down to sorting the wheat from the chaff, having the right system in place, curating data, and finally, using machine learning with an eye towards it being an aid, rather than a replacement for human efforts.