What is data enrichment?
by Zeke Sexauer, on February 5, 2020
Having access to high-quality granular data is mission-critical for any modern brand’s growth strategy. This data fuels digital marketing, analytics, and insight generation, allowing brands to better understand their existing customers, increase lifetime value, acquire new customers, and drive business intelligence efforts.
While all brands get data from their customers, there’s a limit to the amount of information that they can collect without negatively impacting the customer experience. Gaps in customer profiles lowers the efficacy of digital marketing efforts, reduce the return on marketing spend, and limits opportunities for new insights.
To fill in these gaps in their customer profiles, brands use data enrichment.
What is data enrichment?
Data enrichment is the process of appending raw data from external sources to first-party customer records.
Enriching customer records with external sources of data gives brands access to new signal and differentiating information. This allows for the development of unparalleled levels of insights, enabling smarter decisions for growth and product strategy.
With data enrichment, brands can:
- Improve personalization and customer engagement
- Identify unknown site and app visitors
- Build detailed cohorts for lifetime value modeling
- Reduce ad spend waste
- Predict buying behavior
- Boost conversion rates
- Refine targeting
- Create lookalike audiences
How do brands acquire enrichment data?
Typically, there have been two ways for brands to acquire external data for enrichment purposes: partner directly with other data originators or use a third-party service.
Second-party direct deals
When brands need access to raw data, they'll often make deals with other companies to purchase their first-party data directly.
The process by which they select this partner is often known as a data bake-off. Brands will ask suppliers with the data they need to compete for a contract by sending over sample datasets, which the brand will test for accuracy, match rate, overlap, and scale. Once they’ve selected a winning supplier, both companies’ legal teams will draft a contract and negotiate terms and pricing, after which the engineering teams will integrate their systems.
The benefit of this approach is that, by partnering directly with a data originator, brands know exactly how and when the data they're using was collected. This transparency allows brands to execute with confidence, as they can rest assured that the data informing their decisions, strategies, and campaigns meets their specific criteria for accuracy and quality.
This approach does have its downsides, though. Forming these partnerships can take months or even years to complete, and requires involvement from numerous departments, including legal, finance, and engineering.
Furthermore, no one supplier has all the data a brand could ever need, so the process must be repeated every time a brand wants to enrich their customer profiles with a new data type.
As additional sources of data are added to a brand's data portfolio, it becomes increasingly difficult to optimize spend, as issues arise with duplicate data and data that doesn't provide signal.
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Third-party data providers
Third-party data providers solve for this issue of scale by collecting data from numerous entities, aggregating the data into segments, and then reselling it to customers. These segments are typically based on traits like demographics (“men, aged 55-64”), psychographics (“fitness enthusiasts”), or intent (“in the market for new phone”). Brands can then buy relevant segments and match it to their own customer profiles.
The obvious benefit here is the quick access to scale. With one integration, brands get access to a variety of data types from numerous suppliers.
While brands benefit from ease of execution, however, they lose when it comes to transparency. How do third-party data providers classify a consumer as a fitness enthusiast? What is the original source of each data point? How do they test the data for accuracy?
With no way to know the answers to these questions, brands forgo an element of control over their data strategy. They must simply trust the third-party data provider’s methodology.
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A new approach to data enrichment
The typical approaches to acquiring enrichment data come with tradeoffs that limit their effectiveness at powering digital marketing initiatives. To fully realize the value that data enrichment can deliver, brands need to be able to acquire data that is granular and transparent in a fast and scalable way.
Narrative's data collaboration platform provides direct access to an extensive network of raw data providers with software that automates the entire process, helping you increase speed to market, save money, and reduce risk.
With Narrative, you can:
- Access raw data at scale. With just a single integration, Narrative gives you direct access to tens of billions of raw data points across 8 data types from over 40 suppliers.
- Separate signal from noise. Sophisticated filtering options, analytics sandboxes, and automatic deduplication ensures you buy only data that is relevant and actionable.
- Buy with confidence. Know exactly where your data is coming from. While all suppliers are held to strict standards of quality and transparency, Narrative also gives you the resources to do your own due diligence as well.
- Save time and money. Narrative’s tools and workflows automate the time- and labor-intensive processes for finding, purchasing, and activating data, saving your employees time and money on sourcing, negotiations, and integrations.
Interested in learning more about how Narrative can help power your data enrichment strategy? Request a demo today.