Building Your Data Foundation, Part II


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In Part I of Building Your Data Foundation, I alluded to the four critical steps marketers need to take in order build a data foundation. As I said then, you need to define your data strategy and then use these four steps to develop the best, most comprehensive view of your customers. From there, you can analyze, segment, and model your customers and then apply those insights to your programs and campaigns. Trust me, your marketing efforts (and the results they produce) will thank you.

Step One: Identify Your Customers

In B2B marketing, although we market to individuals, we sell to companies. It’s an important distinction. Defining your customer isn’t just about finding a name within an organization; it’s about understanding who within the organization buys the products and services your company sells. As the picture below illustrates, most organizations can have complex structures with multiple hierarchies, locations and departments. In this example, you might want to sell to the purchasing manager within Integrated Defense Systems. And if you understand how the organization works, you can get to that individual, even if you don’t have an individual name, by marketing to the title. Customer Identification

Make sure you understand the inner-workings of the companies you’re targeting, and then use that insight to build your engagement strategy. As a best practice, I recommend mapping this out, especially for the most complex organizations with which you’re dealing.

Step Two: Cleanse and Standardize Your Customer Data

If your data is not clean, you’ll most certainly suffer from deliverability issues, but that’s not all. Irrelevant communications or those that don’t adhere to customer preferences lead to brand mistrust and erosion. Why? Because people don’t like it when you don’t listen.

Data hygiene routines (e.g., address standardization and correction, name standardization, parsing and scrubbing) ensure that you have cleansed and prepared your data as best as possible without compromising the meaning and accuracy of the data. Be sure to develop and incorporate standard or customized libraries that you can update and refine as you go.

Important Tip: Pay special attention to the company name, title and/or contact name. You can clean up terrestrial addresses all you want, but if you’re mailing and don’t know how to properly address the company or person you’re targeting, chances are the people who deliver the mail will toss it in the circular file. Count me as one of those people.

Step Three: Customer Data Matching

B2B data matching is about creating linkages and company hierarchies to gain a better understanding of the organizations and the people within those organizations to whom you’re selling.

If you’re marketing at a company level, you’re going to match at a company level so that you can create unique company profiles. If you’re marketing at a contact level, you’re going to match at that level to facilitate the creation of unique individual profiles. And you’ll create linkages between those and other levels within the organizational hierarchy (e.g., companies to parent companies, locations to individuals and individuals to companies, etc.).

For the matching process to be most effective, a complete history of all records should be kept and used for matching. This allows matches to be made even upon receipt of data that is older, yet with high value and still-relevant attributes (e.g., data captured prior to an acquisition or relocation).

You can match on a number of different variables, but it’s critical to know your source data (i.e., ensure it is credible) as well as the recency of that data. As a best practice, you should refine and test your rules based on results often. In the most advanced matching solutions, prior positive match results can be used to “train” the matching algorithms, much the way you train a neural network.

Step Four: Master Record Creation

So, in steps 1 through 3, you’ve defined your customer, cleansed and standardized your data and run your data matching routines. Now comes the tricky part – creating the “master or optimal record.” It can be complicated to build, but is an important output of all of your data mgmt efforts.

The ‘master record’ is the aggregation and consolidation of data across all sources (prioritized based on a score, where the score commonly includes factors such as credibility of the source and recency and accuracy of the data itself) to give you a more complete picture of your customer. And remember, while we speak logically of a ‘master record’, its really the entire database that must be ‘mastered’ to create this complete picture – many tables, entities and data elements, and the complex relationships between them.

The master record provides both continuity of information, the ability to develop insights and understand behaviors or trends, serve as selection criteria for marketing efforts.

With this information, you can begin to understand how buying decisions are made within an organization. And how to spend your marketing dollars most effectively.

At the end of the day…

I know most marketers cringe when they think about data management – I know I do – but you cannot deny its importance. If I leave you with nothing else, remember this: Building a solid data foundation will make a long-lasting impact on your marketing efforts and lead to a greater return on your investment.

Republished with author's permission from original post.

Michelle Boockoff-Bajdek
Michelle BB brings almost 20 years of technology marketing and marketing services experience to Quaero as the Executive VP of Sales & Marketing. She channels her experience as a consultant into the role of chief evangelist, helping companies understand how to make their data work for them, not against them. Michelle earned her Master's degree from Simmons College.


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