At the beginning of every quarter, while pursuing an upsell or cross-sell opportunities or subscription renewals, it is a never-ending challenge not knowing whether we have reached out to 100% of the applicable customers every quarter, especially when there are product refreshes from vendors.
There is always the 80:20 rule that is universally applicable when it comes to meeting quarterly revenue goals, i.e., 20% of current customers contribute to 80% of the revenue. A fundamental question we ask ourselves, is there a reason why it should be limited to 20% of clients? Why shouldn’t we be looking at the higher top line, i.e. what does it take to bring in the rest of the customers into the revenue fold every quarter?
Before we answer this question, let us take a moment to understand the current challenges.
- It is a challenge to stay on top of the product refreshes from the vendors: Vendors have their unique way of presenting information on the product refreshes, it could be through dedicated portals or by running an email campaign.Alerts on the availability of new content are often ignored. Even the notifications sent by smart sync-and-share platforms like Dropbox, Box, or Sharefile don’t serve the purpose.
- Account managers need to have the expertise to understand the product upgrade or new product rollout and map it to a potential opportunity.
Eventually, if the account managers get their hands on some cool content, they still have to spend time in figuring out whom to send it to. This is how they would do it today: make a mental list of customers, and start writing each one of them an email with attachments. As a result, we are overlooking several customer opportunities.
Using AI and Machine Learning Techniques
The challenges can be addressed by employing AI or machine learning techniques by sales enablement tools. The fundamental components are understanding the customer conversations and having the ability to dynamically map vendor product updates into ongoing customer conversations in real-time. This kind of solution will save the account managers from having to build expertise to understand the solution and spend time in listing the customers who can benefit from it.
An effective AI or machine learning enabled sales enablement tool or “Digital Content Management Solutions for Sales Enablement” should do the following:
- Use engagement dynamics from emails: For an accurate and scalable solution, the content recommendations should be driven toward bringing in the knowledge about the customer from the “Opportunity Management Process,” such as the email. Let the engagement dynamics dictate the recommendations.
- Render actionable recommendations in-line: Bring the recommendations in-line into the account manager’s opportunity pipeline, “Opportunity management process,” such as emails, so that the account managers can stay focused. For greater adoption, artificial Intelligence recommendation engines should do their magic behind the screens and not require the users to adapt to new tools or new practices.
- Provide on-demand curation in customer context: To keep up with the velocity of engagements, content curation should be done within a customer’s context. Give the ability to curate by discussing with the content creator, i.e., vendors or team members, against the backdrop of conversations with the customer to significantly improve the quality of the recommendations.
- Take advantage of the rich EFSS content like Dropbox, Box, OneDrive, Sharefile: It is essential to bring the democratized knowledge that EFSS apps carry into a customer engagement realm seamlessly because the new and relevant content is shared in EFSS apps periodically.
Account managers excel in selling, and sales enablement automation should help them stay focused. Account-based marketing or ABM should play a role in helping account management teams build a credible relationship with customers starting with engaging with valuable content.