The future of ABM is predictive intent
Intent data is a powerful tool for B2B marketers and ABM practitioners. Platforms like Bombora have been providing insights into what companies and accounts are buying using a detailed analysis of intent signals and surges of interest from the web.
However, intent data is limited because it gives a historical view. What B2B marketing practitioners now need is predictive understanding of intent to understand what an account will do in a month’s time, or even a year’s time. From now the race is on to develop that sophisticated understanding of enterprise buying cycles to gain a predictive view of what an account will do in future.
Limitations of intent
Intent data is collected from a variety of sources, including website visits, email engagement, and social media activity. This data can be used to identify accounts that are actively researching a particular product or service and target these accounts with relevant marketing messages.
Intent data is limited because it is a snapshot of past activity. It cannot tell you what an account will do in the future. This is a major limitation for marketers, who need to be able to anticipate the needs of their customers to effectively target them with marketing campaigns. It is said that the best indication of future behaviour is past performance, but for understanding a sales cycle that is not the case.
The need to be predictive
Predictive intent data solves the limitations of traditional intent data by using machine learning, combined with sales data to predict future customer behaviour. Predictive intent data can be used to identify accounts that are most likely to convert in the next 2 weeks, 2 months, or even 6 months down the line.
This information can be used to prioritise sales and marketing efforts, and to target accounts with the most relevant messaging. For example, a B2B software company could use predictive intent to identify accounts that are most likely to be interested in a new product launch. The company could then target these accounts with targeted email campaigns and webinars.
Benefits of predictive intent data
Predictive intent data could offer a number of tangible benefits for B2B marketers including:
- Accurate sales: Predictive intent data can help B2B marketers to identify and target the most qualified leads, resulting in increased accuracy and conversion of sales.
- Improved marketing efficiency: Predictive intent data can help B2B marketers to focus their marketing efforts on the accounts that are most likely to convert, saving time and money.
- Personalised customer experience: Predictive intent data can be used to deliver more personalised marketing messages to customers, leading to improved customer engagement and satisfaction.
Predictive intent is set to become a powerful tool for B2B marketers that can increase sales accuracy and conversion, improve marketing efficiency, and deliver a more personalised customer experience.
In short, it would save a lot of time and marketing spend to accurately forecast when an account will be in-market for a product and for how long, assessing some of the key elements of a sales cycle. For now, bespoke adaptations at enterprise level are the best methods for developing this predictive sales mechanism or route to market.
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