Understanding First-Party Data is the First Step to Gaining Valuable Insight from your Contacts.
While the phrase, “There is gold in them thar hills,” has its genesis in M.F. Stephenson's proclamation from the steps of a Georgia courthouse, Mark Twain actually made it famous with his novel The Gilded Age. The common understanding is that you should find hills that have yet to be mined and then, with some prospecting effort, you will be rewarded. In the 1800s, Stephenson was talking about hills in Georgia rather than the far-off hills of California. Stephenson advocated for mining what is right in front of you.
In this era of data-driven decision-making when we hear so much about first-party, second-party, and third-party data, understanding your first-party data – the gold that is right in front of you – is the first step to gaining valuable insight from your contacts. With that insight, companies can deepen relationships with customers and prospects and make more-informed decisions.
Let’s establish some definitions that summarize the difference between first-, second-, and third-party data:
First-Party Data is data your company has gathered. Often residing in the internal CRM, ERP, and MDM systems, this data is primarily collected from customer and prospect behavior. It can be gathered digitally or manually entered by your employees during sales, marketing, and customer service interactions.
Second-Party Data is another company’s first-party data, and requires a direct relationship with the second party. Think of a credit card company and a car manufacturer that share customer data in order to create a custom offering. While not often seen in the B2B space, there is growing precedence for it, especially with programmatic advertising. Our partner Lotame’s article and infographic offers this easy data breakout.
Third-Party Data is data that can be acquired from a trusted outside party, such as Dun & Bradstreet (which delivers data through our Data Cloud). You are generally able to select data from third parties based on your business need and the insights you’re looking to gain. Data brought in from a third-party data source should demonstrate high standards of data quality, including accuracy, timeliness, completeness, and consistency.
First-party data increases efficiency
First-party data is the bedrock of your data strategy. When merged with third- and second-party data, your data can speed decision-making and increase operational efficiency across departments, regions, and sales channels – and even externally with third parties. By bringing different sources of information together, you can glean additional insight into engagement with customers, prospects, suppliers, vendors, and partners across data platforms. That will help you identify growth opportunities sooner; gain insight into potential risk, fraud, and compliance issues; and create deeper relationships. For example, Dun & Bradstreet’s Live Business Identity is derived from the more than 330 million records that make up our Data Cloud. It provides a comprehensive and continually updated view of businesses.
3 ways to mine your first-party data for gold
So how can you mine your own first-party data to gain the insight needed to reap its benefits?
Here are three ways you can get started:
1) Lookalike Modeling
Lookalike Modeling is a process that involves creating an ideal profile based on your customer or prospect data. There is definitely gold there. Define your best customers, whether that definition is tied to how often they order, how big the orders are, or how loyal they are. Creating an ideal customer profile based on your first-party data is a great place to start for any marketing or sales campaign. You can take this data to an agency or DMP for advertising purposes, create a prospect list for your inside sales team, or mine your installed base for further opportunities.
Dun & Bradstreet can also help you derive insight from your data. Adding our third-party data to yours can help you understand credit risk, get more accurate prospect data, and use corporate hierarchies to know where decisions are made. But without the effort on your part to initially mine your first-party data, you may not uncover any nuggets.
Personalization is often used in the marketing context, but it is also crucial to sales and customer success. Anyone who engages with customers endeavors to make the connection personal in order to deepen the relationship. Personalization is composed of:
- knowing specific information about customers
- accessing and using that information to customize your approach
Marketers like to insert a first name in an email, send an industry-relevant case study, or serve relevant content to their audience on a website. Sales might ask about the customer’s kids, comment on LinkedIn posts, or reminisce about a mutual contact. Customer success does all of this but also remembers that a specific contact is part of a committee to reassess the customer’s technology infrastructure. Because the relationships are spread across your organization, the gold within probably resides in different silos and different platforms. Pull it together, mine it, and disseminate that information across your organization to allow marketing, sales, and customer success to better address your customers and prospects.
By finding the gold in them thar hills, you can:
- Create targeted campaigns and send them directly to the appropriate people
- Pinpoint high-value targets with the greatest chances of closing
- Deliver a warmer, more personalized brand experience to customers
Attribution is the ability to tie a particular marketing or sales action to revenue. Accurate attribution is like a gold miner hitting pay dirt, except that you will never be able to understand all the ways a customer interacts with your brand and attribute a value to every interaction. But you should try to measure it (see my previous post, “The (Unwelcome) Death Knell of First- and Last-Touch Attribution”). In B2B marketing, you need to think about how one action might attribute value to the whole account, not just to one of many stakeholders.
The most common framework for this is account-based marketing (ABM). An account attribution model should be based on your first-party data. Understanding its guidance is the first step for ABM. See our partner Oracle’s page on ABM best practices.
Because attribution within B2B marketing is complex, an advanced attribution model is ideal. Most companies have lead scoring or other measurement methods to track engagement on an individual level. Continue to score attribution on a contact-by-contact level. If needed, pull in third-party data to get a fuller picture of the contacts at an account so you can start to track their engagement.
The next step is aggregating account engagement, and it’s the most difficult. Most tools do not have the “point and click” ability to see who, when, and how all contacts within an account have interacted with your content. If necessary, use the business person’s most valuable tool, Excel, to cross tabulate your top ABM contacts with the top performing assets. There are also software solutions available to solve many attribution questions.
Pay dirt is within your reach
During the mining booms, people would put stakes in the ground to delineate their property from others’. I’m calling on all stakeholders to lasso the data throughout your information silos in order to gain valuable insight into your best opportunities. Put your stake in the ground. Pay dirt is within your reach.
Want to learn more about lassoing data across organizational silos? Check out our video: Mastering Digital Transformation Is About Data, Relationships, and Trust.