It’s hard to believe that account-based marketing (ABM) has existed for roughly twenty years. On one hand, it seems like it’s been around forever. On the other hand, it seems like a relatively new concept that B2B marketers still struggle to adopt. Since its inception, account-based marketing has grown in popularity, and the way marketers handle their approach has matured significantly. Many marketing technologies now support account-driven lead management and new technologies have been developed specifically for account-based marketing efforts. Over time, there has been a greater focus on building properly targeted lists, aligning sales and marketing on the process, and creating tailored experiences for contacts within focal accounts. Data enrichment, intent marketing, and predictive analytics have taken hold, pushing account-based efforts beyond initial expectations.

As marketing evolves and technology advances, account-based marketing takes on fresh approaches and capabilities. Advancements in data management and integration, personalization, content marketing, predictive analytics, and artificial intelligence are changing how we communicate and message contacts (and accounts). Like other marketing efforts, account-based marketing approaches are adapting to provide optimal customer experiences and 1:1 communication.

Three Trends Impacting Account-Based Marketing

Artificial Intelligence and Predictive Analytics in ABM

ABM done right requires tuning in deeply to the needs, actions, and intent of buyers and the organizations for which they work. This requires technologies that allow marketers to listen to the behaviors and actions of their contacts digitally. As these capabilities advance, so does the ability to appropriately target, personalize, and act off this intent information. This leads to cleaner account lists, more focused marketing efforts, and messaging that resonates with buyers when it’s most needed.

Artificial intelligence will play a bigger role in ABM efforts, especially concerning intent marketing. We have already seen several platforms proliferate that specialize in tracking buyer behavior, identifying buying signals, and predicting potential next steps. We will see these capabilities become more critical in ABM as we look to precisely measure intent across buyers in an organization, bubbling up accounts that show the most interest and signals to purchase.

Likewise, we will see the use of predictive models and recommendation engines determine the next best action for these individuals. Technologies that can analyze past and current behaviors, purchases, and buying signals will become more prevalent, and marketers will harness that information to formulate predictive patterns. AI advancements will allow messaging to provide next-best action content and recommendations to advance buyers through the pipeline even faster.

As we’ve already seen, social listening and engagement tools utilizing AI will also begin to positively impact ABM. Most social listening tools can listen for intent, whether purchase, content, or location-based. Sentiment analysis helps us understand how buyers perceive our products, services, and brand. Marketers can use this information and technology to enhance their targeting efforts, funnel buyers to sales and customer service, and personalize messages to help build or regain trust and momentum. Customer experience elevation spans across ABM like traditional B2B marketing, with the added complexity of account experiences in the aggregate. A new level of AI will use these models to predict better account scores, engagement, and intent as technology advances in this space.

Sales and Marketing Collaboration

Sales and marketing alignment has always been a critical component of account-based efforts, and we are seeing even more of its importance as we dive into this next era of ABM. Sales and marketing are coming together, fueling sales enablement through content, intent data, and enhanced lead management. We will see this take a bigger stronghold with account-based marketing, as sales looks to identify which buyers and which accounts are the most optimal to target on any specific day. Content marketing and sales enablement tools designed specifically for certain industries or speaking to particular buyer personas will continue to grow in importance.

Artificial intelligence will assist sales in making intelligent choices in targeting and communication as there are more and more advancements in intent analytics and next-best action predictions. Sales will be fueled with more data than in years past, and it will be important for sales and marketing technologies to help them sort through the volume to find what is truly impactful. AI will become increasingly used to predict the performance of specific actions against certain buyers, helping sales and marketing to reach and activate buyers across stages. Marketing will be able to drive buyers to proper nurture campaigns while sales will have content at their fingertips to help align buyers.

It will also become more pervasive for sales and marketing teams to use cross-collaboration tools to share content such as emails, customer stories, industry use cases, etc. This content will be readily available for marketing and sales. In most cases, sales can use this content to properly message buyers they know have greater intent. Sales messages can be hyper-personalized based on buyer stages, personas, and buying signals. In more advanced platforms, sales and marketing can work together to create prospect and client portals to share information, content, and purchase aids to accounts.

With the aid of AI, lead management will become more sophisticated, driving buyers into various funnel stages, automatically triggering specific nurture campaigns and lead workflows. Predictive analytics will define account scores faster, increasing the speed of lead conversion.

Hyper-personalization

The need for hyper-personalization in today’s marketing world is paramount. ABM is no different. We will see more personalized content provided to buyers within targeted accounts based on their activities, interests, and buying signals. The type of communication they receive, along with the content, will match their needs at the moment and drive them to the next best action or conversion event. Marketing and sales will work together to provide this level of personalization. Marketing channels will use dynamic content within messaging, while sales will gear content to the needs of that specific buyer. As we get closer to 1:1 communication, direct portals and stories may be created for specific accounts and buyers within those accounts.

The use of AI and predictive tools will help make these personalizations even more effective, funneling content into messaging determined by real-time behaviors and interests of the audience. Recommendation engines will be utilized at both the buyer and account levels, ensuring the most relevant content is served. Real-time messaging triggers will become the norm, and buyers will receive content based on their exact needs at the moment. The same holds for post-sale loyalty programs. Trigger-based messaging and predictive tools will further the account relationship and send reminders, follow-ups, and recommendations based on interests and previous purchases.

Bringing Account-Based Marketing Efforts Together

Account-based marketing will follow the same path as most marketing efforts. Artificial intelligence, predictive analytics, hyper-personalization, person-to-person marketing, and real-time messaging will not only become the marketing norm, but will also be expected by target customers. These capabilities are simply taken to the account level with ABM and shared more explicitly between sales and marketing. The further unification of sales and marketing will also drive a greater collaboration to ensure account efforts are optimal and fruitful.

If you want to enhance your account-based marketing efforts, call Relationship One. We are here to help.