Dreamforce 2019 - if data is the new oil, you’re going to need a good refinery

Jessica Twentyman Profile picture for user jtwentyman November 20, 2019
Three Salesforce customers talk about the results they’ve seen from getting inconsistent, incomplete and duplicated B2B customer data into better shape.


As technology industry executives never tire of telling audiences, “Data is the new oil.” The intention, of course, is to position data as an exciting catalyst for innovation and growth, but the similarities don’t end there. Like oil, data often needs a lot of refining before it can be considered a usable product - and that process can be messy, costly and labour-intensive.

Without that work, however, customer data poses particular problems. Inconsistent, incomplete or duplicated records seriously hamper the ability of sales and marketing staff to identify and acquire prospects and then retain them.

At this week’s Dreamforce conference in San Francisco, three Salesforce customers discussed how they have used Dun & Bradstreet’s D&B Optimizer tool to knock their customer data into shape. The tool works by matching and validating a company’s customer data against its own Data Cloud, a broad set of global reference data relating to customers. It also appends data points and analytical insights from that resource, in order to fill in the gaps in information that frequently plague customer data stores.

Lack of trust

Take, for example, Logitech. The company may be best known for its mice, keyboards and gaming equipment, but in recent years, it has expanded into video collaboration kit, such as video conferencing cameras and headsets. This business was worth $260 million per year in its most recent financial year, growing year-on-year at some 42%. Video collaboration is primarily a business-to-business play for the company and Yedda Chew heads up the B2B marketing analytics team there.

Until Logitech used D&D Optimizer, she said, a lack of trust in customer data from three disparate customer databases was a real issue, making it difficult for example to calculate revenues generated by marketing campaigns, as well as cross- and upselling to existing customers.

Data cleansing and enrichment is definitely an iterative process, it’s not a one-time-and-done kind of thing, but we’re excited at where we are today. We can now actually calculate an ROI on a lot of the marketing campaigns that we run and the conversations we are having today with our marketers are a lot more forward-looking. They're focusing on how they strategize conversations versus criticizing the data.

With D&B Optimizer, we’re able to connect those three databases and we’re starting to analyse the buyer’s journey from end to end and get a 360-degree view of it and that allows us to start really getting into more personalization of marketing messaging and understanding what are the trigger points around purchase decisions.

Faltering confidence and disenchantment

Glassdoor, meanwhile, is far more than a platform on which employees can air their grievances against past or present employers – or, to be fair, heap praise upon them. The company also connects employers with promising candidates to fill their vacancies, and has a large sales team working on Salesforce.com to build this part of the business.

According to Swen Kolteman, Director of Enterprise Data Quality, a lack of confidence in the quality of data held in the CRM created two problems for this team: first, it was hard to forecast new business accurately, based on prospect account data; and second, it was difficult to create books of accounts to be distributed to sales execs, based on their sales quotas for the year. In many cases, up to 10% of the accounts in any one book of accounts might be inaccurate, making life difficult (and inefficient) for the sales rep involved:

As a young company, growing quickly, we had those problems, but we didn’t hear a lot about data quality, because we had fewer sales reps with a lot of accounts and they just handled what they could. Now we’re more mature, we have a lot more reps with smaller books of accounts and they scrutinize what they’re given a lot more closely and we’d hear more complaints.

Now that the data has been cleaned using D&B Optimizer, he says, he hears those complaints a lot less.

At Brainshark, a provider of sales enablement tools, director of data operations Kate O’Leary tells a similar story of addressing the disenchantment and low morale that results when sales teams are forced to work with dirty data. At Brainshark, they were forced to do too much extra research on leads and were missing opportunities for cross- and upselling. Using D&B Optimizer for Salesforce, she says, has done much to restore trust and open up new horizons:

We’re now working on linking accounts and clean up our account hierarchies for 2020. And we’re also tackling white space - what industries and companies are missing from our Salesforce. We’re toying with the idea of looking at markets outside of the US. We don’t currently market there, although we do have customers in other regions. What we’re really looking forward to, though, is building an ABM [activity-based marketing] programme around our affiliated customer accounts and we’ve seen some early success with that, so that’s a good step forward and a win for us.

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