This is the second instalment in ‘The Myth of the Data-Driven Organization.’ Here is a link to the first instalment in case you missed it. In this post we’ll explore the factors that prevent high growth companies from realizing their potential, and ways to unlock the goldmine of intelligence in your CRM.
The conversation that launched a product
Late last year I was speaking with a client about their go-to-market approach and how they were planning to re-organize their team. The company was a B2B SaaS provider that was VC-backed and had grown quickly. With a new investor and cash to deploy they wanted to ramp their sales team to maintain high growth. The conversation soon turned to what information they were using to size their total addressable market, identify their ideal customers and allocate their territories. I wanted to understand how they were forming their go-to-market strategy.
“How do you know who you should sell to?” I asked. The Director of Sales Ops shifted uncomfortably in her seat. “We use information from Salesforce…” she said, “but it could be better.”
It was at this point we realised that the client, and many just like them, was facing a more fundamental problem. The client had a bunch of information in their CRM, most of which had been entered manually by the sales team, but it was full of gaps, duplicates and errors. Using the reporting functionality in their CRM never produced the results they wanted because many people had misgivings about the quality of the information underpinning the reports. More importantly, the problem was never going to get better. There wasn’t a carrot or stick that would lead to a sustained behavioral change in the sales team.
Why is this so hard?
The original thread started with another client wanting to integrate the DueDil API into their CRM. Speaking to clients, we found they generally wanted the same thing; a CRM constantly fed with the most accurate and up-to-date information on customers and prospects. Something that would highlight hidden connections and give them insight on their market as it changed. It would be mission control for operationalizing their go-to-market strategy and resource allocation.
We knew the DueDil API could get them closer to this goal. However, integrating it into their existing CRM would have been like turning on a kitchen tap with a sinkful of dirty dishwater. No matter how much fresh water you add, you still wouldn’t want to drink it.
Our clients were sitting on a goldmine of intelligence, with the potential to turn their CRM into a strategic asset. But before they could use insights from their customer data to drive sales, they would first need a way to efficiently clean and enrich the existing information in their CRM.
The half-life of data is shorter than you think
Data management has never been a particularly sexy topic, but the adoption of cloud and APIs has pushed it up the CxO agenda. The volume of data stored by companies is growing on average by 40% per year and continues to decay if it’s not regularly refreshed.
In our world of company intelligence, a recent DueDil Insight Report found that 18% of companies incorporated in the last 3 years have already dissolved. That’s nearly 1 in 5 companies. Aside from the underlying changes in the information, there’s also the challenge of teams creating duplicate records, further skewing sales ops analysis.
Taken together, a combination of data growth, decay and an ever-shifting company landscape means most CRMs will never do what they were designed to do. It’s no wonder that Forrester found that 65% of CRM professionals “struggle to manage the quality of the data in their CRM.”
Don’t confuse objectives and constraints
“As much as I’d like to, I can’t adopt your API until I sort out the data I have in my CRM now,” said our client. “If you can help me solve that problem, I’m in.”
This was the conversation that kicked off months of meetings, engineering effort, fights and feedback sessions to help our client turn her CRM from a liability to a strategic asset. This was the beginning of DueDil DataWorks…
In the next post we’ll tell you more about how we built DataWorks and what we and our clients have learned.