Account-based marketing is now the major arsenal in the majority of B2B marketing efforts. All thanks to the effectiveness of personalized communication to the buyer’s specific needs, it has become pivotal to drive revenue.
Organisations with ABM deployed to look for ways to deepen their engagement with specific accounts. Some companies fail to scale their ABM efforts due to a low grasp of their data.
Data has to do everything with the success of ABM.
B2B companies have huge data pools from their marketing and sales efforts. Data is the crux of carrying out a successful ABM program, focus on aligning and gathering your data into a single data pool to carry out an effective ABM program.
How data makes ABM effective
Data to craft Ideal Customer Profile (ICP)
The most fundamental step to initiate ABM in your company is drafting the Ideal Customer Profile (ICP). The traditional B2B marketing practices negate the importance of understanding account-level information for communication deliverability. The marketing team would send out invites to 1000s of people in the contact list without knowing the best fit profile.
With ABM identifying the best-fit is possible through drafting the ICPs, they get segregated into various personas, industries and journeys. You can read more on ICPs here.
Segmentation and identifying micro-segments
Segmentation is the initiation point of personalization & Targeting. You need to segment target accounts based on the ICP you have created and with the identified best targets. With the existing ICP and customer list, you can use the data to microsegment into various accounts for hyper-personalised content delivery.
Predictive analytics with ABM
When ABM is paired with predictive analytics, it can look for specific behaviour among your audience and enables microsegments. The entire focus of ABM is to design marketing campaigns to grab the attention of target accounts. Doing this requires high-level account level and individual level intelligence. This intelligence requires intent data to offer predictive real-time analytics. Introducing data models and services with Artificial Intelligence (AI) to offer predictive insights. This can enable your teams to be ahead of your buyer journey and optimize the entire ABM process.
Data facilitates sales and marketing alignment
With ABM, the efforts of sales and marketing coincide and they don’t work as silos.
34% of organisations engaging with ABM reported that their sales and marketing teams are very much aligned. Since marketing and sales should focus on collaborative efforts, it is essential to work with the right data. Having the right data ensures that the teams are on the same page at all times. Your organisation can use data to assign values and segment accounts with engagement and proximity to ICP as factors. Another aspect of data in ABM with team management is shared reporting, since all the teams have the access to the same data, it becomes handy to infer and solve challenges. Hence data enables open and effective communications across the teams.
Measuring ABM performance
With all the necessary data being collated and analyzed, it is best to tell what’s working and what’s not. Comparing Key Performance Indicators (KPIs) from all the activities from the ABM efforts would enable you to keep track and compare. Here are some performance KPIs -
- account penetration
- deal-to-close time
- win rate
- annual contract value (ACV).
ABM campaigns fail and succeed depending on how well you collate data and make the best use of it. Be it segmentation, personalization and prediction, data is the key. If you want to learn more about executing data-based ABM programs, talk to us.