The 5 Use Cases of Predictive ABM

The 5 Use Cases of Predictive ABM

By Daniil Karp, Content Marketing, 6sense

One of the main appeals of account based marketing (ABM) is that, unlike inbound marketing tactics that have defined B2B marketing over the past five years, ABM is a proactive strategy. ABM targets high-value accounts, delivers customized messaging and allows marketers to track their impact on bringing in large deals and helping close marquee upsell opportunities. A true ABM strategy will touch every part of your lead-to-revenue process, remaking the way your marketing and sales teams drive growth for your business.

What is Driving ABM Adoption?

The forces driving ABM adoption include (i) advances in technology, (ii) access to an ever-growing B2B network of customer data, and (iii) a more competitive, customer-driven business landscape.

On the technology and data side, ABM as a strategy is attainable today. Advances in analytics and data gathering techniques have allowed ABM to achieve enterprise-level scalability. Historically, ABM meant a team of sales executives and creatives working a small number of accounts to deliver a very expensive, white-glove service to the most strategic and high-value prospects. Today, technology enables the creation of a long-tail of target accounts. Paired with marketing automation, B2B marketers can apply an ABM level of service to a larger portion of the market.

On the business side, the confluence of 2 forces is driving ABM adoption. First, as digital marketing tactics mature within B2B companies, competition and consolidation in many industries are forcing marketing teams to take on a new level of revenue accountability. Second, the consumerization of the B2B experience is driving customer expectations for service and personalized support on par with B2C brands.

The 5 Use Cases of Predictive-Powered ABM:

To respond to theses forces and implement ABM, modern companies will need to adopt advanced predictive intelligence techniques into their marketing and sales processes. But, as you’ll see below, none of these approaches are new, just honed and automated with data-driven decision-making.

Select and refine your target accounts
Traditionally, creating target account lists focused on using the insights of sales teams and identifying the general demographic characteristics of your existing or desired client base. While there is value in mining the market knowledge of your sales team and using basic demographic models, both these approaches have diminishing returns.

To sustain continuous improvement, marketing teams must use customer data and predictive intelligence to verify sales-identified target accounts and augment segments that are based on static demographic criteria. Using customer intent data stored in your marketing and sales systems can allow you to identify target accounts exhibiting behavior linked to opportunity creation in the past. Including data from the broader B2B web enables identification of in-market accounts who do not look like your existing client base to uncover new markets.

Building your target account list on continuously monitored, behavioral data allows you to iterate on how you identify target accounts. Companies who find ways to track the market and follow the needs and trends driving the evolution of their customers are more successful in the long-term.

Gain visibility into buying committees
What separates your target account list from the broader world of prospects is insight – your ability to understand the decision-making structures and business challenges of your strategic accounts. Traditionally this has been accomplished by your marketing and sales team digging into the organizational structure of your target accounts. Knowing the economic buyers, decision makers, influencers and end-users is vital to making a strong case for your product. Over the past 5 years, advances in outbound SDR tactics and the rise of tools like LinkedIn Navigator have taken prospecting to new heights.

Today, predictive intelligence can help automate and put data behind your preferred buying committee by analyzing historic opportunity data and identifying your best champions in an organization. Companies can also set behavioral triggers that signal buying activity based on the research habits of individuals on and off their site. This added insight can help identify those leads most likely to turn into a new opportunity. Finally, based on your in-market target account lists, predictive intelligence can identify the gaps in your database and help coordinate your lead generation efforts.

Align efforts for sales and marketing
The defining feature of ABM is a high level of coordination between marketing and sales. The issue has always been that such coordination is labor intensive, resource expensive and highly un-scalable. While your marketing and sales teams are most likely already tag teaming on your most important accounts, how can you bring that same level of intelligence to the next tier of one thousand companies that will no doubt account for a vital part of your revenue pipeline?

Predictive intelligence can help automate key handoffs between marketing and sales to offer a higher level of customer service to accounts that show they’re ready for later stage conversations. Firstly, using product-level buying intent data marketing can create a specific service level agreement with sales development teams that account for highly in-market accounts. This will help focus costly sales development time on accounts most likely to convert into clients. Similarly, knowing which accounts are in-market can help marketing target their strongest customer acceleration content where it will make the most impact.

For target accounts that are exhibiting strong buying behaviors, marketing and sales teams can also define auto-qualified leads (AQLs) rules, which route specific leads directly to your strongest sales executives, bypassing lengthy qualification processes. When your strongest sales leaders can get into accounts earlier, they can increase the deal size and shorten the sales cycle.

Tailor messaging and content targeting
Focused messaging is the lynchpin of an ABM strategy. Putting the wrong name in an email or sending a strategic account messaging that has nothing to do with their business can make an account disengage or cost you a relationship with an important decision maker.

The foundation of an ABM approach to content and messaging starts at the general market level and moves all the way to buyer personas and account-specific messaging. As you move up the ladder, the level of difficultly and the tax on your marketing resources grows exponentially. Few organizations have the resources to create the content necessary to offer their tier one and tier two accounts a level of personalization and targeting that truly accelerates the buying process.

Predictive intelligence can help you bring that level of relevance to a much longer tail of targeted accounts. As advanced organizations move to omni-channel marketing, having your website, email and outbound experience aligned by target account, buying stage, and business challenge is vital to keep prospects engaged with your brand and sales team. Implementing a predictive intelligence engine that is constantly listening to signals from your web log activity, marketing automation and CRM also allows you to continually inform your marketing content and messaging based on live conversion rates. This allows your marketing team to begin to bring to your long tail of target accounts the kind of customization and relevancy normally only available to your tier-1 accounts.

Focus campaign planning and channel budgeting
Account-focused media and marketing campaigns are truly beginning to come into their own in 2016. Companies like Terminus are offering ABM display advertising campaigns and ads can now be served based on a companies specific IP address.

Predictive intelligence can help take these efforts to new heights. New technologies and B2B web visibility are allowing companies to achieve new levels of messaging consistency across mediums. No matter how prospects from a specific account choose to interact with your brand across your digital properties, they’ll find on-message content that speaks to their specific needs and tailored value proposition. With a growing number of media partners, you’ll also be able to bring this level of targeting to your best performing media partners like Forbes.

Finally, it will also allow you to smartly leverage your outbound and inbound tactics based on those accounts who are at the right stage of the buying process for additional research or a deeper conversation about implementation.

If you’re interested in learning more about relevant use cases, check out our Predictive-Powered ABM presentation with Carol Krol of DemandGen Report.

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