In March, Mintigo scored big in Account Based Marketing (ABM) by announcing innovative predictive analytics solution for Marketo. We caught up with Tony Yang, VP of Demand Generation and Marketing Operations at Mintigo, to understand more about Account-Based Marketing and the impact of predictive data science, audience profiling and location analytics on the latest “sweet” #martech topic for every marketer.
MTS: What do you mean by Total Addressable Market (TAM) in ABM?
Tony Yang (Tony): Here’s how I think about these two terms.
For ABM, one of the critical first steps is to identify the right set of target accounts to focus on. TOPO Senior Analyst Eric Wittlake discussed in his presentation at the recent Revenue Summit event that a best practice is to allocate at least double the resources between tiers in a three-tiered ABM approach.
So, selecting the right accounts is extremely important because an effective and comprehensive ABM strategy can become extremely resource intensive – you don’t want to waste budget and efforts on trying to reach a target company that will never buy from you!
ABM 3 tier approach to your "target market" (target list due diligence) emphasis on high value accounts #TOPOsummit pic.twitter.com/p4hIAq0CrD
— Jennifer Pelfini (@jmpelfini) April 12, 2017
To reduce the risk of selecting the wrong accounts, you’ll want to identify what your Ideal Customer Profile (ICP) looks like so you can better understand the characteristics of your best and most valuable customer accounts. There are plenty of resources on the web that discusses how to define your ICP (such as this framework from TOPO), and a predictive analytics solution such as Mintigo (the company I work for) can certainly help you quickly and easily identify your ICP. But, the point is that you need to take a more data-driven approach to selecting target accounts instead of throwing darts at the latest Inc 5000 list to pick your target accounts.
Read Also: Mintigo Delivers Unique AI-Powered Integration for SAP C4C and SAP Hybris Marketing
Once you figure out your ICP, you can then see which companies match that profile. Depending on your predictive analytics solution provider, you may be able to overlay that ICP on top of the known universe of companies that you know about (typically in your CRM or marketing automation database) as well as those that you didn’t know about yet (we call these “net new accounts” at Mintigo).
Recommended Read: Demandbase Expands Online ABM Certification Program for B2B Marketers
The sum of these two sets would be your Total Addressable Market (TAM). Now you probably wouldn’t choose all the companies within your TAM as target accounts just yet because they could number in the thousands depending on your industry, criteria, etc.
ABM playbook depends on type of customer #TOPOsummit pic.twitter.com/HDjamv1Wmy
— Jennifer Pelfini (@jmpelfini) April 12, 2017
You’ll want to select a subset of accounts within your TAM as your target account list, and you will probably refresh this list every few quarters or so. A few ideas that we like to recommend to clients is to select the accounts that have demonstrated “intent” in the categories that your product sells into, and/or to identify the ones that have the highest revenue potential.
MTS: Where do you see Location analytics and people-based marketing fitting into ABM strategies in 2017?
Tony:
Even though the “A” in ABM stands for accounts, you are engaging with people at these target accounts – you can’t lose sight of this when you are implementing campaigns in your ABM strategy. Marketers like to talk about personas of their buyers (or more likely, those in the buying center within an account) which is a good practice to help you understand the pain points, challenges, and needs of these people so that you can help solve their problems with your solution.
Remember that their problems you are helping them solve for represent the broader needs of their company…and in the context of ICP characteristics as a target account. With multiple people in a buying center, your messages should resonate in this manner to each person.
In terms of location analytics, I see this as an important piece when targeting enterprise accounts that will very likely have multiple office locations and remote workers.
Understanding where your target contacts are located enables you to reach them using high-touch, personalized and white-glove types of tactics such as creative direct mail packages, face-to-face events/workshops/meetups, leveraging locally-based channel partners, etc.
MTS: How is customer engagement strategy for a marketer different from that of sales pros? Or, is it the same, thanks to ABM?
Tony:
An effective ABM strategy requires buy-in and alignment from various stakeholders in your organization, including but not only limited to those in marketing and sales. However, each group has a different role to play for obvious reasons.
For example, marketing can help provide air cover via social or display ads, generate top-of-the-funnel demand using target account content syndication, create personalized web and email content experiences, etc. All these activities help support Sales so that when they make a call into a target account, there’s a greater chance of engagement because it’s not a cold call.
MTS: How can marketers use predictive analytics for CRM data cleansing and data standardization? What’s the ideal roadmap for CRM users to do it effectively?
Tony:
Data cleanliness and standardization should be an aspiration for every marketer regardless of whether or not they are pursuing an ABM approach. The earlier you start getting a solid handle on your data architecture (i.e., what you want to track, relationships between objects and data fields within these objects, what data type, taxonomies, what kind of time-based/temporal data, where the data should live, any potential workflows and validation rules, etc.) the less painful it will be. It’s sort of like dental hygiene! The longer you wait, the more painful it will become when you address it later.
Some predictive analytics vendors offer a data cleansing and enrichment component as part of their solution, and other don’t. I recommend that you ask about this with your preferred vendor, and get into some of the specifics that I mentioned above.
MTS: What’s the message to B2B enterprises that neither uses Predictive Analytics nor ABM in their stack?
Tony:
First of all, ABM is not a good approach for all B2B enterprises. It really depends on the type of customer you sell into, how long is the sales cycle, what’s the ASP, etc. For example, one of my previous companies was a B2B social e-learning SaaS solution. We offered a freemium version/30 day free trial and our most common pricing plans ranged from $15/month to $500/month. Most people pay via a credit card. An ABM approach would not have made sense for that kind of scenario.
Predictive analytics has a broader value story though. Depending on the use-case, you can employ predictive to help prioritize leads if you have a large amount of lead flow that you want to help determine the good from the bad. We’ve already discussed predictive in the context of ABM, though I will also mention that the insights gleaned from predictive and the data from the models can help drive more intelligent engagement with target accounts across marketing channels and sales conversations.
We just published a new white paper with David Raab on this topic called “Embedding Predictive Analytics in Account Based Marketing”. You can even utilize predictive to identify potentially churning customers. I recommend discussing your needs with your predictive vendor to discover how the technology can help solve a particular need that you have.
MTS: Thank You, Tony, for answering our queries on ABM. This was informative and we hope to see you back on MarTech Series very soon.
Beginner’s Guide to ABM: How to do Account-Based Marketing in 2017
