The continued rise of big data poses a unique problem for business owners and marketeers. As digital footprints increase allowing for more and more accurate, insightful customer data to be gathered, businesses are suffering from information overload. A recent study by Forrester revealed that 62% of businesses surveyed have more data than they can process and are not able to use all their data when making decisions. As a result, 82% believe adopting AI for marketing via predictive marketing is essential for business success .
Below, the experts at Think Beyond outline the benefits of adopting a predictive marketing approach and why getting big on data gets you ahead in B2B.
The Benefits of Predictive Marketing
The predictive marketing “cure” prescribes the following. Leverage your past and present data with the latest in AI, mathematical algorithms and machine learning to forecast future behaviour. As a result, you determine which marketing action has the best chance of success.
As a strategy based on intent, predictive analytics deliver the following distinct benefits:
Engaging new audiences
The intent based nature of predictive marketing means not relying solely upon past purchases and buyer personas for audience targeting. The creation of predictive affinity audiences, such as in Google Ads and Facebook, allow extended targeting without sacrificing relevancy. This means that you can attract leads you didn’t even know you had.
Real-time touch points to accelerate pipeline velocity
Ultra-targeted content comes as standard with predictive marketing. Working in “micro moments”, predictive technologies serve up real-time personalised content in the most appropriate form. This pushes prospects further down the funnel and deliver cross-sell and up-sell opportunities. From email to web pop-ups to in-app messaging and more, predictive campaigns are tailored to an individual buyer’s cadences.
Predictive behaviour models to reduce wastage
Predictive lead scoring helps to minimise wastage and protect the bottom line through identifying which leads are most likely to convert. Sales teams can therefore concentrate efforts on the hottest prospects. This creates an efficient and productive path from MQL (marketing qualified lead) to SQL (sales qualified lead).
Similarly, predictive customer lifetime value modelling helps to funnel marketing spend into long-term profitable areas. Through browsing history and site visit frequency for example, businesses can create and market to audience segments deemed to have a high lifetime value.
Predictive marketing has no expiry date. Unlike remarketing that has a limited shelf life and targets only those known to you, predictive analytics provides a constantly evolving audience base. Working across marketing channels and devices, predictive technology takes every data point, lead score and customer models to inform audience selection and buyer behaviour. In this sense, predictive marketing is self-renewing; today’s audiences build tomorrow’s insights.
Why the B2B future is AI marketing
With 86% of businesses set to increase their use of predictive marketing , the applications are especially valuable to B2B. Specifically, long purchase cycles and high acquisition costs often threaten to blow the marketing budget.
From how likely a prospect is to purchase to delivering the right content at the right time to the right persona and more, the value of predictive analytics lies in lean. In particular, creating a lean and efficient spend at each stage of the sales funnel and for every customer journey. Able to attract, nurture and convert prospects based on intent, predictive marketing helps you get ahead and stay ahead. Early adopters in B2B are reporting increased lead quality, conversions and deal size .
Getting big on your data therefore means to get big with your marketing strategy.
To discuss AI and predictive marketing, call now on 01625 682110 or submit your contact details online to request a call back.
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