Businesses collect lots of customer data. To get customer insights and make data-driven decisions, marketing and sales teams need to acquire data from a range of different sources, channels, platforms, and touchpoints. Later on, it is often quite challenging to pull this data together and merge it in a single storage. This is where data stitching comes to the rescue.
Data stitching allows you to make sense of all the collected data and, in turn, helps you build more targeted strategies and offer a better experience to your customers.
Data stitching defined
Data stitching is the process of combining different sets of related data into one common destination. There, the data can be merged, aggregated, summarized, and processed in many different ways. The end goal, most often, is deriving valuable insights, building extensive customer profiles, or merging data from different business entities into a single report.
Marketing professionals, for example, can be interested in pulling data from all their channels and merging it all together for a general report. Accountants, on the other hand, would gladly combine reports from the different business entities they manage into a single destination. Check out this article to find a detailed case study of using data stitching for business.
While data stitching can be done manually by simply exporting data from apps regularly and uploading that into Excel, for example, it’s not feasible at all on a larger scale. Luckily, there are a number of tools capable of stitching the data from the apps you use on an automated basis, with little or no coding necessary.
Why does data stitching even matter?
While stitching data may seem like a nice addition, for many professions it has become nearly a necessity. Without it, they’re missing out on tons of valuable information and end up misinterpreting facts or guessing more often than they would like to.
To understand why, let’s look at a simple example. Marketers crave any information they can get about their customers. They want to know about every touchpoint, every click on an ad or a button, every interaction with their website, and so on. All this information is somewhere but it’s spread across different apps or accounts.
A potential customer, let’s name her Jane, clicks on a Facebook ad that pops up on her wall. Jane checks out the landing page an ad leads to, reads more about a business, and then leaves. A few days later Jane types in the website address one more time but this time on her mobile phone. She explores a bit further and eventually makes a purchase.
Many Janes later, the team looks at the data for each channel separately. Checking their Facebook Ads account, they see a very low conversion from that ad running lately so they decide to discontinue it and focus their efforts elsewhere. Meanwhile, Jane and many like her continue using the product thanks to that very ad they saw on Facebook.
Stitching data from Facebook Ads and Google Analytics would allow the marketing team to connect both visits and correctly attribute the user acquisition to the social media platform. The metrics they rely on would have looked differently and so would likely their business decisions.
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