Consumer data is like a freshly picked flower. As soon as it is gathered, it starts to degrade and grow old.
This is why marketers spend an average of 14.5 hours a week managing customer data collection – to keep it fresh. Yet it can take weeks to convert a prospect into a customer, during which a lot of that data can spoil.
Indeed, poor-quality data costs companies an average of nearly $13 million each annually, Gartner reports Data enrichment can preserve marketing investments and improve ROI.
If you are a marketing executive, data analytics professional or part of a business development team wrestling with the challenges of incomplete or lackluster customer prospect data, this guide can help.
What is Data Enrichment?
Let’s start on the ground floor. Before you can enrich data, you have to practice basic data hygiene. That means monitoring your datasets to remove inaccuracies and duplicate information (think out-of-date contact information and misspellings), and ensuring accuracy and reliability.
The better your data hygiene, the better prepared it is for data enrichment, which is pretty much what it sounds like: adding complementary information to existing data sets so they more precisely represent your target market. This supplemental information can come from internal and external sources, but the goal is to fill in gaps and provide more context.
For example, the insights can include the socio-economic data associated with a prospective customer’s address, or recent purchase and browsing histories that indicate interests.
This context is essential for anticipating prospective customer preferences and personalizing the customer experience accordingly. Two-thirds of customers want brands to recognize their personal needs and expectations, HubSpot reports, yet nearly half of businesses say data enrichment and completeness is the leading barrier to realizing data-marketing success.
How Data Enrichment Benefits Marketing
Data enrichment improves marketing performance by filling in important missing pieces of your customer profiles. When you blend these intentionally-selected external insights with your internal data sources, you get improved target marketing.
Among the key benefits of data enrichment services:
More accurate and thorough customer profiles. Consumer lifestyles, needs and routines change, so yesterday’s profile data won’t necessarily reflect the customer today. Enriched data derived from public records, surveys and social media can keep pace with customers more comprehensively. The resulting profiles are more reliable, which not only improves efficiency by saving time but builds a brand’s reputation for caring.
Heightened personalization and customer experience. The combined insights of enriched data can make sense of behavioral complexities, helping you understand your customers deeply enough to craft more spot-on campaigns. This effort can improve sales: 73% of consumers expect better personalization as technology improves, according to Salesforce. And, importantly, the enriched data can help you avoid missed sales opportunities.
More sophisticated segmentation and targeting. The advanced learnings that result from data enrichment can enable you to segment prospect markets using a wider criteria, such as psychographic data, postal codes and opinions, and customize campaigns accordingly. A prospect at a rural address might respond to certain imagery and words differently than a prospect at an urban address, for example.
Boost Engagement with These Data Enrichment Strategies. To achieve the above benefits, you will need a process for carrying out the task of data enrichment. These fundamental techniques can position companies in varying industries for enriched engagement:
Purge and append. This exercise is one part housecleaning and one part updating. To clean the data sets, perform a full audit to remove buggy information, such as incorrect and duplicate entries. Then single out the information gaps; they will point to the data sources that can stand to be enriched. Add the missing data that fills in those knowledge gaps.
Bring in third-parties. This technique answers the question of where to get the missing data. If your internal insights come up short, incorporate information from sources that do not directly interact with your prospects. Third-party data, which is available on data marketplaces, can include weather information, public demographics and government and academic records.
Train the learning machine. If your platform includes machine-learning capabilities, feed your enriched data sets into those algorithms. They will analyze the insights, collate behavioral patterns, and then embellish customer profile data, based on its predictions. If your platform does not include machine learning, you can use cloud-based services or hire a third-party service.
Essential Data Enrichment Practices
Whether you’re selling technology, pharmaceuticals or flowers, these common best practices should be applied regardless of the type of data you collect and your marketing strategy:
Ensure data privacy and compliance. Draw up a governance policy for collecting, storing, protecting and disposing of data, one that adheres to protection regulations (such as GDPR and CCPA). For compliance as well as quality checks, keep records of all data sources, the enrichment processes and how decisions are made.
Perform regular quality checks and updates. Set a schedule to regularly inspect the data enrichment process to ensure profile quality (meaning timeliness, consistency, completeness). In between inspections, consider installing an automation tool that can perform updates in real-time. This will streamline the audit process.
Build a marketing and IT alliance. Marketing relies heavily on IT for its data analytics and reporting, so it’s practical that the two departments work as a team. A “no-walls” policy between the departments should encourage more opportunities for each to learn from the other’s skills as well as challenges. Consider contests and incentives, perhaps a rewards program, for improved marketing campaigns.
Building Better Customer Profiles Through Enriched Data. In this step, be mindful of simply what data should go into building a customer profile, based on your product. Once the best-aligned data insights are chosen, the following exercises will ensure they are securely put to work.
Make sure you have the right sources for your need. Not just in terms of the necessary information to be integrated into profiles (purchase history, social media profiles, demographics), but also in the technology that will incorporate the enriched data. If you lack the software or platform to manage the enrichment process, several third parties exist.
Integrate data enrichment into existing systems. This process involves combining the external data sources with your existing data sets. It needs to be seamless and exacting in order for the merged data to come out cohesive and accurate. Data integration tools and software can automate this process. Once complete, validate the data to ensure it meet standards.
Measure your data-enrichment results. Establish key performance benchmarks for the post-data enrichment process, such as conversion rates, and regularly measure them to ensure they are meeting or exceeding target. Doing so can alert you to weak spots in the processes as well as opportunities for where to redirect your marketing message.
Unlocking the Benefits of Data Enrichment
Research from Dataversity shows that data enrichment can contribute to a 40% gain in sales through improved lead quality. Following are other examples of how a well-integrated data enrichment plan can boost company performance.
Improved customer segmentation. Enriched data ensures more precise customer categorization because it synthesizes disparate data to produce more distinguishing criteria, such as family interests, website interactions, purchase frequency and community. Market messaging can then be tailored to select segments.
Increased revenue through personalized marketing. Enriched segmentation enables organizations to deliver individualized customer communications that are more likely to produce results, such as well-timed product recommendations. Personalization such as this can boost revenue by 5% to 15% and improve return on investment by 10% to 30%, McKinsey reports.
Streamlined customer support. Data enrichment tools can update your datasets automatically by continuously cross-referencing them with other sources. This fluidity eliminates potential blips in customer relations, because customer support employees have quick access to the most up-date-date, relevant customer information – not only name, but past purchases and other preferences.
Enjoy the Riches of Enrichment
How fast does data age? For some prospects, key pieces of information may have changed in the time it took to read this article. Data enrichment preserves the quality of your data and keeps it fresh, ultimately improving the quality of your marketing efforts.
If you’re interested in learning about how data enrichment can support your organization, visit our Data Enrichment Services website.