Most B2B purchasing decisions, especially high-cost purchases, often involve a number of internal consultations with several individuals within a company. And the more people involved in a purchasing decision, the less likely a purchase will be made.
These days, buyers do more research. According to MarketingProfs, 94 percent of buyers conduct some form of research before buying a business product. And for 90 percent of buyers, the time spent on research is price dependent. In other words, the higher the price, the more time spent on researching the product. In addition, many buyers will not contact the supplier until 57 percent of the purchase is complete.
This trend is set to continue with both Forrester and Gartner predicting 80 percent of B2B purchases will be made without human interaction in 2020. B2B buyer expectations have changed, thanks to rising prominence of various IoTs. Buyers now prefer to interact with B2B brands through a range of channels, similarly to how B2C buyers interact with a brand.
Since it is now becoming more difficult for B2B marketers to generate leads, what can B2B marketers do to overcome this challenge? The solution is Account-based Marketing.
Account-based Marketing (ABM) is a B2B marketing technique that focuses on an account, or company, rather than the individual. Marketers using ABM invest time in familiarising with a specific account or company and identify their key business decision-makers. Once these decision-makers have been identified, marketers can then approach them either directly or indirectly with inbound or outbound marketing techniques.
ABM involves marketing techniques that are tailored toward attracting key business-decision makers within an “account” or company. These techniques call for a strict focus on the specific needs of those specific decision-makers. The key to finding these key decision-makers involves thorough research of a company and identify possible post-holders or personas involved in purchasing B2B products. The next step is to investigate where these decision-makers spend most of their time online and then go on to create appropriate content and make it available through their favored online media channels.
The key to a successful ABM campaign lies in its ability to approach the key decision-makers on their own terms. This approach often ensures that the vital decision-makers receive the message that addresses their needs, using channels that they use, and delivering a message that they're almost sure to see.
With inbound marketing, marketers focus on reaching as many potential customers as possible with their content. The “funnel” narrows down the wider audience into prospects, then down to potential buyers, and finally down to actual paying customers. While the inbound approach reaches a wider audience, the percentage of actual customers at the end of the funnel is small. It’s certainly not a bad approach, but it shouldn’t be solely relied upon.
The ABM approach turns that funnel upside-down. Instead of focusing on delivering a broad message to a wide audience, ABM marketers use a tightly-focused message relevant to a decision-maker, or a small set of decision makers, in an account or company. For companies that offer specific services to a niche audience, the ABM approach is often a better use of their marketing efforts. As Vice President of Research at marketing research firm SiriusDecisions Megan Heuer said, “If you believe ABM success is measured only on lead volume … think again. ABM is about influence.”
ABM offers numerous benefits, both for marketers and for sales teams. Outside of targeting highly specific companies that would be your ideal customers or clients, here’s a breakdown of why ABM is useful:
According to marketing services provider MRP, one of the most vital components in launching an ABM campaign is what is known as “predictive analytics”. This set of analytical methods includes techniques from data mining, statistical modeling, and machine learning to build a predictive model of the behavior of customers that fit the ideal customer profile. As with any marketing strategy, the development and implementation of an ABM approach starts with analyzing data from prospective customers.
However, not just any data will do. MRP recommends the use of “intent data”, which it defines as a combination of internal and external data that gives marketers “a more expanded view of buying intent in (the) target market.” The internal data can come from sources such as surveys or CRM (customer relationship management) solutions, while the external data can come from third-party sources, such as publisher data and ad exchanges.
Marketers can employ ABM methods to target one of two audiences: new prospects or existing customers. ABM techniques can help sales and marketing staffs find prospects that use similar channels and have similar needs to their existing high-value customers. The “look-alike” modeling method uses data from companies whose behaviors resemble those of current customers and lets marketers develop similar messages through the same channels at the same point in the prospect's purchasing cycle.
Marketers can also use ABM methods to prioritize their efforts in approaching current clients with new products or services. ABM campaigns can target the most active clients, or those who make the biggest purchases, or those whose purchasing cycles coincide with the campaign's launch dates. These methods help the sales staff maximize the revenue potential of their top clients.
The principles of ABM sound simple: find the key decision-makers within an account, find their preferred marketing channels, and target them accordingly. However, the implementation of these principles can present its own set of challenges, especially if the sales and marketing departments work less like partners and more like separate entities. It’s important to overcome any internal silos to make this strategy worthwhile.
As for being worthwhile, the results often speak for themselves. According to Marketo, 97 percent of marketers engaging in ABM report that it has a higher rate of ROI than any other marketing initiative.
What’s your ABM strategy looking like?
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Predictive analytics, or predictive analysis, is a form of analytics that lets you forecast future events based on historical data. It combines statistical algorithms, AI and machine learning to analyze and learn from past customer actions