Hands up if the following scenario sounds familiar to you: You’re a demand gen marketer, and you just can’t get enough qualified leads to satisfy your sales team. So you commission a B2B data vendor to help you do some serious outbound marketing.
You know they’re good because they’ve been recommended to you, plus they’re pretty well known in general. It seems like a safe bet.
A few weeks (months?) later, and — it worked! Now you’ve got more leads than ever before! More leads than you even know what to do with. Life is good.
Only… wait… you can’t do anything at all with the vast majority of them, because they don’t actually fit any of your customer profiles. They’re totally useless.
Now, not only do you still not have enough qualified leads, but you’re practically swimming in junk data.
After working tirelessly to cleanse your Marketing Automation Platform and/or CRM of all the unusable data, you’re almost back to square one. To top it all off, Sales are giving you more grief now than they were before this all started.
This scenario is currently playing out in B2B companies big and small, across pretty much every industry. And it’s not just a frustrating waste of time and money: having too much of the wrong data is arguably worse than not having enough data at all. It simply creates more, needless work, increases the pressure on marketing, and creates or exacerbates tension with sales.
So why does it happen?
Ninjas and Superheros
To a great extent, the above scenario results from a lack of understanding of what counts as useful data.
For example, many data vendors will ask you to select contacts by job titles — which is problematic for a number of reasons.
To start with, the days when people’s job titles provided a reasonable idea of what they actually do are long gone.
Between all the Evangelists, Rock Stars, Ninjas, Growth Hackers and Superheros, you’d be forgiven for thinking the B2B world is… well, far more exciting than it actually is. More importantly, when otherwise serious potential buyers are using increasingly silly (or just plane ambiguous) job titles, you can’t rely on that information alone to market or sell to them.
But it’s more than that. You may regularly sell to prospects with refreshingly descriptive titles — like VP Sales, or CFOs, or Directors of IT, or CMOs, or Heads of HR — but that doesn’t mean everyone with the same title will be interested in your product.
Leads are people, not data sets. They might share job titles, but they could still be different in almost every other way. For example, they might
- Be in a totally different industry;
- Have that pain-point addressed already via a different solution;
- Lack the necessary budget;
- Be far too big/small to be relevant;
- Work with incompatible technology;
- Be the perfect fit — but unaware of the need for your solution, so in need of careful nurturing;
- Be otherwise unwilling or unable to purchase, for any one or more of one hundred other factors.
(By the way, you can put you hands down now. I can’t see them anyway.)
So what constitutes “useful” data?
Given that your contacts are human, the data and insights you gather about them should be too.
All of the above factors should be considered: industry, familiar and existing technologies, company size, geographic location, and job functions (as opposed to titles).
That last criterion is highly illustrative. You don’t just need to know what their job is called — you need to know what they actually do. Most importantly, you need to know if their job function includes having the necessary buying power to close a sale.
Beyond what you need to know about them, there’s also the how — or, more precisely, the where. As in, where is your data vendor drawing those insights from?
Your potential customers exist over multiple channels. They likely use two or more social media platforms, and they might blog as well. Their professional information could be available in one place, their personal and contact details somewhere else, and their social media/online behavior somewhere else again. What’s more, some of those sources of information could be outdated or inaccurate, and may therefore be contradictory.
When you consider all of that, is it any wonder that turning to a single data channel will at best yield limited results? To understand your leads you need the full picture.
Multiple vendors isn’t the solution
But do you really want (read: have the head or budget) to manage several different data vendors, cross-check the various results, and then manually update your systems every few days?
No, of course not. Yet, frustratingly for all the demand gen people out there, this is too often the only choice that’s available.
The thing is, it isn’t.
In an increasingly sophisticated and competitive martech industry, there’s no excuse for clunky and inefficient anymore. Efficient demand gen requires an omni-channel “single source of truth“, which automates the data-gathering process, bringing together insights from all the relevant sources (first- and third-party data, unstructured social data, the open web, etc.) and verifying them for you.
That frees your marketing and sales teams to do what they do best — unburdened by the Sisyphean task of data maintenance, and no longer tempted to compensate by data-hoarding.
That’s what HR outsourcing company Zuman did. After traditional data vendors proved more trouble than they were worth, Zuman quickly turned to a much smarter solution — one which doubled the number of meetings booked by their sales team, and increased pre-MQL lead engagement by 45%.
Read the free case study below for the full story:
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