Account-based marketing (ABM) focuses a vendors marketing and sales resources and efforts on specific customer or prospect accounts that will likely gain them the most business. It differs from traditional marketing approaches where marketing is typically organized by industry or product/solution. ABM merges all these divisions and uses them to focus on the most profitable accounts.
Although ABM is an old concept, it recently has become a proven, must-have in modern marketing. According to various studies, 92% of B2B marketers consider ABM “extremely” or “very” important to their marketing efforts.
Until recently, marketers used static account lists, built either using basic intent data, lookalike modelling, or by analyzing customer characteristics such as geographic information and company size. Although proven efficient, compared to traditional methods, these lists require manual periodical update and refresh, giving enough room for improvement.
Intent data may come either internally (1st party data) or externally (3rd party data) from various data providers. They are voluminous and complex and need to be cleansed and consolidated in order to become useful.
Artificial intelligence-powered marketing automation makes intent data exploitable and data-driven marketing models effective:
Automated marketing workflows and processes, such as natural language processing, personalized messaging, and content delivery, provide the agility and effectiveness. Additionally, you want automation to help save marketing resources by automating regular daily tasks and help boost exploitations in intent data uncovered.
Due to the fact that on a daily basis, quintillions of bytes are processed:
Contrary to the traditional approach where prospects may belong to accounts of interest, the simple guiding principle behind account based marketing is:
Choosing key accounts is a two-step process:
Building ideal customer profiles is the most strategic part of choosing key accounts and implementing account-based marketing since it incorporates your organization's marketing and sales strategy into specific keys and metrics. Depending on the segmentation, several ideal customer profiles may be defined.
Key accounts may include existing or potential customers level of profitability, operating industry, geographical information, demographics, size and other similar information. They may include actual measurable information as well as trends and estimations.
You can compare and rank your marketing prospects and techniques once you have adequately defined your ideal customer profiles and interest segmentation. Back office systems such as CRM or ERP may provide structured information for your existing customers, while 3rd party data providing your prospects and leads.
In order to focus on the active demand, you should gather and properly interpret your intent data
As data gathered is voluminous and complex, information should be extracted and interpreted through big data analytics and techniques after data cleansing and consolidation.
Organizations with clearly defined customer profiles and prospects of interest can more effectively engage their customers with personalized marketing strategies and content.
Personalization tailors relevant data to the customers at the most individual level. It is strongly dependant on data availability. This segmentation can be considered as aggregating common personalized features as well.
During the early stages of the customer buying cycle, where there is no sufficient data to build an effective personalized strategy, content or message delivery based on segmentation is the solution. Depending on the importance and your needs, in ABM really personalized services enable marketers to focus on individuals customers and ensure the optimum customer engagement.
Delivering personalized content to accounts, prospects and customers, is the cornerstone of successful customer engagement. Gartner implies that in 2018 organizations that invest in personalized content should outsell more than 20% from those who do not, and other studies imply that personalized content is more effective that impersonalized by 80% in B2B.
Content management platforms and content-as-a-service platforms are used to deliver smart personalized content without demanding huge investments. Additionally CaaS platforms provide omnichannel features where content is personalized and delivered regardless of the device that the consumer uses.
Recommendation Engines (or systems) is a subclass of an information filtering system that aims to predict the preference of an account user into an item, based on intent data. It acts as an intelligent salesman who knows the customer behavior and can make intelligent decisions about what recommendations should benefit the customer most. Recommendation engines are widely used in content management systems.
Content management platforms take intent data as input (both 1st and 3rd party) and based on topic priorities, recommendation results and content ROI should deliver smart and personalized content.
Other personalized marketing services that contribute to customer engagement may include personalized advertising either in search engines or social media or personalized account automated communication through the entire customer journey.
A final step in an account based marketing program is to evaluate, review, and improve, if necessary, the program performance. Tracking and easily measured KPIs, such as engagement levels, conversion rates, ROI, and loyalty along with correspondence to personalized marketing, time spent to websites, portals, etc., can be used to determine whether account based program is performing well.
Usually the corrective actions should be taken in defining the ideal customer profiles, since this is a process that is performed manually and has the major impact on successive ones. Other areas that may need improvement, such as predictive analysis performance or content performance, can be easily analyzed, since they refer to a small group of high yield accounts.
Account based marketing has been an agile and measurable marketing approach for generating new customers and increasing revenue from existing ones. Marketing automation powered with artificial intelligence, along with technology improvements, have boosted the effectiveness of an account based marketing program implementation.