When you are using DATA in your marketing operations there is a possibility that you’ll see a 15% increment in your Marketing ROI.
Securing high value client is a dream of every business out there, and ABM helps you focus on those high value clients than rather opting for broader reach. ABM filters out your marketing operations to individual accounts, which leads to higher engagement, relevant messaging and ultimately better conversion rate.
Account-Based Marketing circles around data analytics, which increases the precision in targeting and positioning of a campaign which effectively transcends into to conversion of key accounts. In this further read you’ll get the deeper insight of how data really works for lead, starting with…
The Role of Data Analytics in ABM
Data analytics is the arm of ABM strategy. It helps marketers to sort insights from large volume of data, so that they can take more informed decisions and further assist personalized marketing.
To increase the marketer’s ability to identify high value accounts, integration of data analytics into ABM is very viable, it helps them to understand the needs and behavior of the prospects and helps them deliver more personalized experience.
1. Identifying High-Value Accounts
Data analytics helps you out with the identification of accounts which are more likely to reflect a significant revenue. Data goes through historical data market trends, and predictive analysis to denote companies the ICPs. Examining factors like company size, industry, revenue and their engagement history with the help of predictive analysis, gives an edge to the businesses.
2. Understanding Account Needs and Behaviors
After identifying high-value accounts, it is important to understand their particular needs and behaviors. Insight into the pain points, interests, and buying behavior of these accounts can be gained through data analytics.
By assessing different sources of information like social media activity, website interactions, customer relationship management (CRM) systems among others, marketers can have a better understanding of what makes each account unique.
3. Delivering Personalized Content and Experiences
ABM cannot work perfectly without personalized content; hence data analysis becomes very crucial in this context. Using information about the likes and dislikes as well as account behavior patterns, marketers are able to create personalized messages that are appealing to specific decision makers within targeted companies. This method increases chances for one-on-one interaction with a client and consequently leads to more sales conversions.
Applying Data Analytics to ABM
Implementing data analytics in ABM goes through several essential stages starting with data collection and integration, analysis and then action.
Below is an overview of these stages.
1. Data Collection and Integration
Leveraging data analytics for ABM begins by collecting data from diverse sources which include first-party (e.g., CRM, website analytics), second-party (e.g., partner data) and third-party (e.g., market research, data vendors). This requires integrating these sources into a single system that can be analyzed holistically.
2. Data Analysis and Insight Generation
Analysis follows after the process of collecting and integrating the available information. The use of advanced analytic techniques such as machine learning, predictive analytics, and natural language processing helps uncover patterns that guide ABM strategies. These methods are used to segment accounts, predict future behaviors, and identify engagement opportunities.
Predictive analytics, for instance, may indicate which accounts are expected to convert leading sales while machine learning algorithms can identify types of contents that resonate with specific accounts.
According to a Forbes report, firms that use data analytics in their marketing realize a 15% increase in marketing ROI. This highlights the impact of data analytics on marketing performance as it indicates an improved ROI.
3. Insights and Execution that can be acted upon
The last phase is converting insights into action. Here we take advantage of the insights from data analysis for informing and optimizing ABM campaigns. Marketers can develop targeted content, personalized outreach and customized experiences based on the insight-driven information.
Marketing automation platforms and CRM systems are highly significant in doing this work. They enable marketers automate personalized outreach, gauge engagement levels during campaigns and measure their success rate.
Recent study has found that ABM generated the highest return on investment (ROI) for 76% of marketers compared to other marketing strategies. These metrics demonstrate the tangible benefits of integrating data analytics with ABM execution.
Examples and Case Studies
Some organizations have been able to utilize data analytics in order to achieve precision of ABM.
Highlighted below are a few cases that stand out:
1. IBM
IBM engages in advanced data analytics to identify and prioritize high-value accounts. IBM can segment accounts according to their potential worth by using these data, which comes from multiple sources, and this will enable them customize their marketing efforts accordingly.
2. Adobe
Predictive analysis is a driving force behind Adobe’s ABM approach that aims at understanding the needs and behaviors of target customers.
(Source: Adobe)
In Conclusion
Data analytics has gone on to facilitate accurate targeting in Account-Based Marketing (ABM). By being able to identify high value accounts, understand what they need and how they behave as well as delivering personalized contents and experiences, marketers can scale up the effectiveness of their ABM strategies significantly.
On the other hand, integrating data analytics into ABM processes enhances targeting, engagement drives higher conversion rates and leads revenue growth.
Well, this is an enough of wakeup call, use data and apply it to ABM today, Connect with us at Vereigen Media today!
By Akash Bhagwat
