We B2B marketers are a simple breed. We don’t ask for much. Some good leads now and again; enough SQLs to keep sales from chewing our ears off; license to throw around some silly acronyms every so often.
We’re easy to please.
But alas, it’s all easier said than done.
When you’re not working thanklessly to conjure qualified leads from nowhere, you’re drowning in a sea of unqualified leads and accounts, wondering where on earth all this junk came from – and what whoever put it there expected you to do with it.
Sound depressingly familiar? Well, you can draw some solace in knowing that pretty much every B2B company struggles with the same lead gen problems. Marketers in businesses big and small alike are dreaming wistfully of a time when data quality is no longer a problem and they’re armed with enough good leads to deliver qualified accounts and leads to sales consistently.
And, hey, at least 90% of your inbound leads aren’t totally useless! (If they are, don’t panic! Just read on…)
Support.com is a leading provider of cloud-based software and services that delivers next-generation technical support. They’re also a former consumer-facing company, which began as a personal-computer troubleshooting product and service provider, and later switched to a B2B model after achieving enormous success selling enterprise cloud software.
The problem: the consumers never got that particular memo. They continued to flock in their millions to their website and fill in lead generation forms, seeking personal technical solutions.
As a result, thousands of unqualified leads were flooding into their sales and marketing databases, to the point that 90% of leads in Support.com’s systems were completely irrelevant.
Needless to say, sales complained – a lot – which was annoying enough. But worse still, since the lead qualification process was entirely manual, marketing ops spent an infuriatingly long 24 hours (!) to qualify a lead.
You know what every marketer in that position wants to do? Adopt account-based marketing, just to mix things up. So, they did.
Now, their already overwhelmed marketing team needed targeted lead lists ASAP – which they weren’t likely to get a lot of the way things stood.
Back to basics: All marketing should be data-driven marketing
In truth, Support.com’s implementation of ABM was actually an illustration of its appreciation for the importance of targeted, data-driven marketing. So naturally, they went back to basics: their data.
Data-driven marketing sounds like a buzzword (well actually it is), but in today’s data-saturated lead gen environment there really is no avoiding it. Data needs to be at the center of every demand gen activity you do, from content marketing and social media to marketing and sales ops. With account-based marketing that’s perhaps truer than otherwise, given ABM’s emphasis on targeting select (named) accounts and zeroing in on the few individual influencers within those accounts to make the sale. To embark on that kind of pinpoint strategy you need plenty of up-to-date, accurate, relevant data.
Using real-time data enrichment, Support.com were able to qualify and route all inbound leads immediately, instead of 24 hours.
Rather than make do with basic insights like job title, company location or size, each lead was appended with dozens of granular insights including job functions, company revenue, industry, and familiar technologies. This made it much easier for marketing to assess which leads were truly likely to buy; which in turn meant more genuinely qualified leads to sales; which in turn meant a lot less complaining. In fact, their sales and marketing teams were aligned like never before – and even… got on well…!
With that level of intelligence, they were also able to create effective and accurate buyer personas to prospect for net new – again with a high level of accuracy.
At the end of it all, Support.com reduced their average sales cycle by 67%; whittled down the time to qualify leads to almost nothing; and enabled their teams to compile target lead and account lists for ABM in just days.
How exactly did they do all this? Read the full case study below to find out more:
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