Developments in revenue operations and intelligence technology have led to a proliferation of technology investments for B2B sellers. Understanding what needs each revenue growth ai vendor serves, and what features overlap between vendors, helps leaders avoid misallocation of time and budget when making technology investments. One study from Mckinsey and Company found that, “Managers at a typical Fortune 500 company may waste more than 500,000 days a year on ineffective decision making.” Here we explore the most important features for revenue growth AI technology as described by Forrester’s report, New Tech: Revenue Operations AndIntelligence, Q4 2021, and elaborate on how Aptivio addresses these essential functionality elements, making the decision easy for managers.
The functionality of revenue growth AI serves to accomplish three main objectives:
· Engagement and Productivity Optimization
· Rev Ops Cadence and Forecast Optimization
· Revenue Engine Analysis and Optimization
The table below produced by Forrester illustrates the degree of success each functionality segment contributes to accomplishing those objectives for B2B sellers through analysis of industry vendors.
Aptivio Segment Functionality
Nonhuman Digital Buyer Interactions
Nonhuman digital buyer interactions occur when a user engages with a digital platform without interacting with another end user. For example, think of a user performing a search operation on a website, or clicking on a demo video. At present, late-stage vendors lack appropriate signal arrays to accurately capture and depict this intent data. As a result impacts in each objective category suffer.
Insights for Account Retention and Expansion
While current revenue growth AI vendors identify opportunities, they lack adequate insights for account planning, retention, and expansion. Signals that indicate the potential growth or atrophy of an account are important for forecasting and strategizing how to follow up on accounts. Without these insights, end-users miss opportunities that grow sales revenue.
Insight into Buying Group Membership and Role
Because buying groups are manifested through predetermined arrays of intent signals, end-users are left working with incomplete or inaccurate buying group members and role information. Without a more granular perspective of who comprises buyer groups, and the roles of opportunities within buying groups, end-users are unaware of if their buying groups capture the full scope of personas they target. Inaccurate targeting or insufficient targeting hinders efforts to optimize key objective areas.
Insight Into Buyer Behavior and Preferences
Once leads convert into buyers’ revenue growth AI vendors don’t provide insight into the behavior or preferences of those buyers. Failing to address those preferences, or understand buyer behavior, risks churn as buyers' expectations are not met.
Dynamic Engagement and Activity Guidance
The appropriate course of action for following up on the insights delivered by revenue growth AI vendors is not always clear. To drive the most value possible from existing data pools, intelligent orchestration needs to be coupled with action prescriptions. Subjective decision-making on how to follow up on leads inhibits revenue growth as sales funnel dropouts are not mitigated.
Aptivio consolidates pertinent data for revenue operations alignment into a single, easily navigable, revenue growth AI engine. Guiding sales and marketing teams through buyer journeys by equipping them with an all-encompassing resource for revenue operations positions organizations for success. Explore our website here for information on the results we drive for our clients. To learn more about buyer intent AI and how Aptivio is disrupting the revenue growth AI industry, click here.