Data Enrichment: The Alchemy of Data Transformation?
Data enrichment can provide substantial value to marketers. But why and how? Writing exclusively for ExchangeWire, Peter Silverwood (pictured below), chief scientific officer, iotec explains that data enrichment can transform vast quantities of data, but the key is for marketers to know what they want from their data before embarking on the journey.
Marketers are well aware that good quality data has become mandatory across every aspect of their work. One aspect is to ensure a marketing campaign reaches a relevant target audience.
What if you want to do more than just target? What if your brand wants to get more granular targeting using extra data, and to derive insight from the results? That’s where data enrichment comes into play.
At its simplest, data enrichment can work like a spell-check – sifting your information and adding in new information. But enrichment does more than that – it can provide a more informed basis for the whole marketing mix.
The core information of a standard mailshot campaign is an address, used to send to perhaps thousands of recipients. But, today, marketers can enrich that single data source with others that might connect those address postcodes with demographic, intent, or earnings data.
Suddenly, a financial services company doesn’t have to send its flyer for its retirement-planning service to everyone in a post code but, instead, only to those known to be on the cusp of retirement and within a particular net worth bracket. That makes for more refined targeting and better results.
These kinds of additions can be used not just for targeting but for the insight that informs targeting. Did your campaign resonate best with 60-somethings or 40-somethings? With men or with women? The answer relies on holding data that is enriched beyond a single dimension and can make future efforts more efficient.
This is a kind of alchemy, turning base raw materials into something far more appealing. But how does the transformation occur?
It is often the case that organisations are sitting on more data than they realise. What seems like a single data set can, when really probed, turn out to be several others, perhaps from different divisions, that can be blended in to comprise a more informed whole.
Peter Silverwood, Chief Scientific Officer, iotec
Data sets can also be bought in from commercial warehouses like Experian and Acxiom. But many marketers are surprised to learn the value in freely available public data from the likes of Office for National Statistics, which allow them to cross-reference ward-level census data, or from Ofcom, which allow a mobile phone brand to examine smartphone penetration, for example.
So, how do you enrich your data to best effect?
Data management platform (DMP) vendors claim their software suites are the optimum way to combine data pools. But they won’t typically employ the intelligence of machine learning to help marketers understand what worked, and which paths to follow next.
The first step to enrichment is simply to ask a question. Now that you’ve got data, what do you want to learn?
Whilst, for those working with relatively small data in spreadsheets, a simple pivot table may be a viable starting point to find the answer, the sheer volume of data available to marketers today means extra powers are required.
Savvy marketers will already have employed a data scientist to help. Data scientists are not just spreadsheet monkeys, nor simply technical coders, although they will have both skills at their fingertips. They are focused on business outcomes – and, whilst that means getting their hands dirty with data and numbers, it also means deriving and communicating the insights that are unlocked when data collides.
The prerequisite to all this, however, is integrity. If your customer data is poor-quality, incomplete or disunited, you don’t have the raw materials that can make for transformative results. The old saying about “garbage in, garbage out” is true.
And with this quality data we can then do away with assumption-based marketing and instead focus on what is really happening for your audience. More granular data allows you to see beyond an homogenous audience to the individual. An assumption free audience of one is the ultimate goal, and forms the basis of intent marketing.
Data enrichment is the way ahead. But to make this alchemy work, quality, granularity, and intelligence are key.
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