From a strategy perspective, enterprises are still at the initial stages of ABM adoption. And, to reach maturity, ABM needs to be infused with predictive insights
An ITSMA research showed that about half of ABM programs are nearly a year old, with about 17% being in place for over three years. However, ABM adoption is expected to get a boost in the coming years, due to enterprises decreasing the traditional marketing budget by almost 50%.
The real challenge that enterprises foresee is to figure out how to reach the next stage of ABM — balancing personalization and budget. That’s precisely where intent data and predictive insights come into play.
The Future is about Merging Predictive Insights with ABM
The purpose of account-based marketing is to work on strategies designed to address the needs of individual target accounts. And, for these, firms require a deep pool of intelligence at both the individual and account levels.
Many of the B2B marketers are turning to third-party intent data purchase to understand the true needs and behaviors of the in-market target accounts. Infusing this customer information into the ABM strategy will unleash the power of targeting with better content and higher conversion rates.
To achieve the advanced level of ABM, intent insights need to be predictive to offer critical information in real-time. The intent data partners are leveraging artificial intelligence (AI) to unlock advanced predictive insights. AI is the need of the hour for business owners to stay ahead of buyer expectations by optimizing the ABM processes further.
By leveraging intent data and predictive analytics, businesses can boost ABM performance with the below three key benefits:
- Better Account Prioritization: The key factor in ABM is “timing.” Even if the target account list is accurate, misjudging when they’re actually in-market can result in low conversions and wasted marketing budgets. But, with intent data and predictive insights, marketers can have real-time intelligence of the accounts which are most likely to get converted. This streamlines account prioritization to optimize the budget allocation fully.
- Deeper Content Personalization: The main reason why personalization is such a massive challenge for ABM practitioners is that they often react to account intelligence. Predictive analytics helps marketers to go beyond the buyer behavior of customers, giving them the means to personalize content to minimize the wastage of marketing resources proactively.
- Accurate Intent Signal Scoring: Intent signal scoring should go hand-in-hand with real-time intelligence. As accounts and contacts move along the buyer’s journey, predictive analytics help marketers to project the best opportunity for sales outreach. Without predictive intent insights, competitors could reach target accounts before, or the messages could become outdated.
B2B marketers are aware of the potential benefits of bringing AI to the ABM program — but they are struggling to implement it successfully. Investing in intent data sets built on predictive analytics and ML without understanding the underlying technologies will lead to failure. Businesses need to know what to look for from an intent data provider in order to be successful.
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