Part 1: Cracking the account centric demand gen code – a 4-step process
Given our market focus is on delivering global, account-based marketing solutions for some of the world’s largest and most innovative B2B brands, our customers expect us to be able to build demand generation programs that intelligently identify and target likely buyers for their (often considered purchase) products and solutions. So far, so good. But if finding ‘likely buyers’ was straightforward, then there would be no need for the multi-billion dollar market dedicated to marketing technology, customer profiling and data interrogation.
In B2B marketing, there are typically two types of audience to target:
(i) A defined set of accounts that broadly fulfil the criteria required to be classed as a potential buyer
(ii) A certain type of economic buyer, or particular job title, that could exist in a significant number of accounts
Each ‘ask’ requires a different approach and in the next two blogs, I’m going to explain how to be successful for each of them. For this, initial blogpost, I’m going to focus on defining a list of target accounts. But before we get into describing HOW to pick the right set of accounts, let’s begin by looking at WHY it’s so important to get this right.
As discussed, finding likely buyers is far from straightforward. Indeed, account list selection is very, very easy to get wrong. And the problem is, when you get it wrong, it’s extremely difficult to rectify further down the line. Once campaigns have been activated, if the results don’t come back as expected, there are so many variables to consider in the analysis around those unexpected results, that it becomes a highly complex, near impossible task to find sufficient evidence to point at the account list being the cause. And, in addition to the complexity, is the time and budget already invested in the campaign which will have been wasted. If you get poor results because you targeted the wrong accounts, this will only become evident when sales have already worked the leads, by which time the programme will likely have finished and the investment fruitless.
So that’s the bad news! The good news is that there are tools and data available to ensure you focus your time and money on the right audience. Here is our four step process to selecting, identifying and prioritizing your target account list:
Step 1: Account selection:
Look at the information you have in-house already
Begin by analysing the data you have on existing customers and prospects you’re targeting. This does not need to be scientific, but can be anecdotal evidence too. Talk to your Sales and account teams to get their views and, ultimately, try to turn this information into something that is analysable and searchable. Developing or referencing an Ideal Customer Profile (ICP) can be helpful for categorising current customers by size, sector, pain point, and identifying commonalities
Create a list of ‘good’ accounts
Establish what you think ‘good’ looks like. Once you’ve looked at the information you have available, analyse the profile of your best performing accounts as you begin to build your account list. What are the common features of these accounts? It’s a good idea to have these existing accounts as a benchmark to refer back to. Also consider any significant blockers to progress within existing accounts and whether there are correlations with identifiable characteristics of accounts that could be used as exclusions when building your target account list.
Step 2: Account Identification
This initial list of benchmark accounts can now be extended by cross referencing key characteristics of these accounts with firmographic data, looking for commonalities. These may include:
– Size: does the account meet the target size criteria?
– Geos – does the account’s geographical presence meet requirements?
– Industry – is the account in an industry that we consider to be suitable for this programme?
– Personas – can we identify relevant stakeholders that could be reached within this account? (more about this in next week’s blog)
Step 3: Account Prioritization:
Adding these accounts to the list of benchmark accounts means you now likely have a significant list of target accounts. But this list now needs to be honed using further data sources, such as intent data, in order to create a final – yet dynamic – target account list.
Understanding which accounts are demonstrating interest in the subject matter you are dealing with will be useful when looking at the potential value in them as clients and whether they should be included in your campaign. Similarly, data which reveals which accounts are already working with direct competitors or industry partners (which partners, and to what extent?) is valuable.
Once you have your dynamic list of accounts, it’s important to weight the data available in order to prioritize your accounts. For example, you might have an account that only just meets the numeric criteria, such as company size or revenue, and therefore returns a low score for this category, but is equally showing incredible indicators that it’s the right type of customer in terms of intent. In this instance, your scoring model should elevate this account above one that scores highly on company size and revenue, but is showing no suggestion that it might be right for you at that time.
Step 4: Testing the account list
Before launching full-scale activation of your strategy, carry out an experiment with a small proportion of your budget to assess whether you’re likely to get the results you’re looking for from these accounts. This could involve using multiple channels and tactics to measure general reach and engagement across your target account list. Use this data to identify hard-to-reach accounts and refine your approach to either exclude these accounts to focus on easier-to-reach accounts, or potentially employ different channels to reach them with your messaging.
Once you have your dynamic list of accounts, you can activate campaigns to measure engagement and impact on a continuous loop. Which accounts or vertical sectors didn’t respond? Was the messaging or channel used the right one? Or was it simply due to these accounts using another solution that they’re happy with? If so, move those accounts out and move other accounts in. As the name dynamic suggests, it’s not a static model and can be assessed and optimized on a regular basis.
Demand generation is the antidote to silos between sales and marketing, but this begins with the intelligent identification and selection of likely buyers of your solution. For further information about how to do this, contact us at email@example.com