The driving force behind a business’s digital transformation is data. So, it’s appropriate that businesses appear to be creating and holding more of it than ever. One report says that 39% of businesses have 50 or more databases of contact data – a considerable increase from 10% in 2014.
But is this really a good thing? After all, this ever-growing mountain of big data needs to do much more than simply exist. Marketers also face the challenge of having to understand it, extract it and use it.
Yet even with the tools and talent in place, there is still an elephant in the room that must be addressed: data quality.
Data quality is a problem that cannot be underestimated. In the travel industry it is a huge obstacle to an organisation’s capabilities and strategy, with nearly half (46%) of data professionals saying data quality and cleanliness is their biggest challenge. Others says working with inaccurate or out-of-date customer data is costing them one in five customers each year. Ask data scientists and they’ll say cleansing data is the most time-consuming and least enjoyable aspect of their job.
The causes of poor quality data
A key step towards making data fit for purpose is uniformity. Most databases were not created with the intention of being used for anything other than their original purpose. This is also means that different repositories store different types of information, or use different identifiers for the same type of information.
For example, a retailer’s database might contain products identified by a description, by their own SKU code or the original manufacturer’s product ID. This can be the same for names and addresses. All of these identifiers make sense in one situation but not in another.
Moreover, by being separate, it means no one data storage location contains all the information you might need. In the past, businesses have attempted to solve this by placing all their data within a single repository. Yet this only really solves part of the problem. A far bigger issue is that this vast warehouse of data is now just a mass of inconsistent files formats, variable naming conventions and replicated data.
Worse still, there is nothing to say that this data – whatever its format – is even accurate. Both B2B and B2C data has a limited shelf life and its expiry can be brought about by name, address and job titles changes, permission changes, and so on. Data entry mistakes like inaccurate or missing fields can mean it was never correct in the first place.
So, it may well be big data, but it certainly isn’t clever, and marketers will find it very hard to put it to any real constructive use. True, better data governance at the point of collection can nip a few problems at the bud, but if you hope to use this data for marketing campaigns, direct mailings, personalisation strategies – even more cutting-edge tricks like predictive technologies and AI systems like chat bots – the intelligence they are using will be fundamentally flawed.
How do you ensure data quality?
Sorting your data quality means laying a trustworthy groundwork for your big data strategies. This means deduplicating and merging records, introducing consistency to their format to be machine readable and identifying the data that is now out-of-date, redundant and non-compliant.
Data cleansing is the ideal way to take stock of where you stand, and, for a short while, you’ll see an immediate uplift in your marketing performance. But, as we’ve covered, you cannot escape data decay.
This is why obtaining a Single Customer View is so desirable. This process feeds cleansed and deduped data from all your data silos (along with additional enhancements from third parties) into one database fit for marketing to create the much sought-after ‘golden record’. Plus, it does so continually, ensuring the value of new data you introduce and maintaining what is already there.
Data quality isn’t a trivial matter and improving it more than a ‘good’ thing you should do. It’s the most essential component for every one of your data-driven marketing efforts.
Blue Sheep Data Quality Audits
Thousands of marketers use the Blue Sheep Data Quality Audit to assess and improve the health of their marketing data.
This free service can be used as a one-time assessment of your marketing data quality, or as the first step on a partnership with Blue Sheep towards an insights driven marketing team.