Bridging the ‘product knowledge’ gap

It is no secret that product teams are constantly pushing out new features, enhancements, and updates to stay ahead of the competition. With GenAI enabling teams to code faster, this pace has become all the more breakneck. 

While these rapid innovations are crucial for maintaining a competitive edge, they often create unintended challenges for account executives (AEs) and solution engineers (SEs).

These folks are, without doubt, the frontline representatives of your company. They not only have to sell the product but also address customer queries, identify pain points, and tailor solutions that meet unique business needs. 

However, when product teams release updates at insane, never-before-seen speed, AEs and SEs find themselves out of the loop, struggling to speak confidently about the latest features or integrate them effectively into their sales pitches. This disconnect can hinder sales performance, affect the brand, reduce morale, and negatively impact the overall effectiveness of your go-to-market strategy. 

As McKinsey notes, sellers need to invest extensive time in developing deep industry knowledge and product expertise. This is where GenAI comes in. It can boost research efforts and provide critical insights quickly, helping sellers serve customers across diverse industries, geographies, and cultures. 

Knowledge that previously required hours of research or even years of experience to acquire can now be obtained on the go, right on the sales call (if need be).

But we are getting ahead of ourselves. Let’s talk a bit about this growing challenge first. 

Why does this product knowledge gap exist?

It is no secret that the SaaS ecosystem has always thrived on agility — weekly sprints, bi-weekly releases, continuous deployment, you get the drift. This agility is what set it apart from the old world of ‘here’s a CD for X software’.  

However, AI has accelerated the already quick pace. While this means products evolve rapidly to meet customer demands, it simultaneously creates an information bottleneck for sales teams. Existing knowledge management systems struggle to keep up with this accelerated pace of change.

Imagine this scenario: a product team rolls out a new feature that significantly improves data analytics capabilities after customer feedback and, as a result, addresses a major pain point for several high-profile prospects. 

Suppose the account executives and solution engineers aren’t made aware of this enhancement promptly in a context they can understand. In that case, they miss an opportunity to showcase a valuable solution during their sales conversations. Worse yet, they may appear uninformed when quizzed about this. 

This scenario brings forth a few problem statements:

• Volume of information: Frequent product upgrades mean a constant influx of new information. It’s challenging for teams to keep up with every new feature, bug fix, or enhancement, especially when they are juggling multiple accounts and deals across various sales funnel stages.
• Lack of context: Product teams often communicate updates in technical terms or broad release notes that don’t translate easily into customer-centric benefits. The frontline teams need contextual understanding to relate features back to specific customer pain points, given that their audience might not be technical.
• Inadequate communication channels: Many organizations lack streamlined processes to ensure that product updates are communicated effectively to sales teams. Relying on lengthy emails or dense documentation can lead to important information being overlooked.

How can you bridge the product knowledge gap?

Implementing the right AI sales tools and developing a comprehensive sales enablement strategy can help address these challenges. 

Create a centralized knowledge hub

It is important to develop a single source of truth where all product updates are documented in a way that’s accessible and easy to navigate. AI-powered sales assistants can enable access to this knowledge base right from communication tools like Slack and Microsoft Teams. 

Translate features into benefits

‍Product teams should collaborate with sales enablement or marketing teams to translate technical updates into customer-centric language. This means clearly outlining how each new feature addresses specific use cases or pain points.

Hold regular cross-functional syncs

‍Company leadership must ensure that regular meetings are scheduled between product and sales teams. These could be bi-weekly or monthly sessions where product managers demo new features, explain their value, and answer any questions from the sales team.

Provide microlearning modules

Instead of overwhelming AEs and SEs with long documents or presentations, provide bite-sized learning modules focusing on new features. Short videos, say, made with Loom, quick reference guides, or even interactive quizzes, can make it easier for them to absorb information.

Ensure real-time updates and alerts

‍Use tools like Slack, Microsoft Teams, or CRM notifications to send real-time alerts about critical product updates. This ensures that they are immediately informed about changes that could impact their ongoing deals.‍

Set up feedback loops

‍Encourage AEs and SEs to provide feedback on how product updates are resonating with customers. This two-way communication helps product teams refine features and prioritize future developments based on real-world insights.

Leverage AI-powered tools

‍AI platforms, like SiftHub, can play a crucial role in streamlining this process. 80% of reps working on teams using AI say it’s easy to get the customer insights they need to close deals, compared to just 54% at organizations without AI. Also, Hubspot’s survey reveals that 64% of surveyed salespeople who use AI to automate manual tasks save 1–5 hours per week. 

These advanced AI sales tools represent the future of knowledge management. These tools can automatically surface relevant product updates based on active accounts and ongoing deals. 

By using AI to filter and contextualize information, AEs and solution engineers receive only the most pertinent updates, reducing information overload and ensuring they can confidently address customer needs.

BCG observes that rather than using AI in place of sales reps, leaders can use GenAI to assist them by providing a digital support team, specifically, four sales personas: a talented sales assistant who can brief reps before every call, a data scientist who can help reps find new prospects, a personal marketer that can polish and personalize emails, and a wise sales coach that can help reps become top performers. This support will improve efficiency.

The benefits of keeping AEs in the loop

According to Salesforce, non-selling tasks, such as administrative work and meeting preparation, consume 70% of reps’ time. As you can guess, without time carved out for critical selling efforts, reps struggle to connect with customers.

A well-executed, AI-powered sales enablement strategy, supported by effective knowledge management systems, will go a long way.  

When account executives and solution engineers are well-informed about product updates, the entire organization reaps significant advantages. 

AEs and SEs can confidently address customer queries and proactively present new features that align with customer needs, creating more meaningful customer conversations. This also means that they can demonstrate value more quickly, which often results in shorter sales cycles and faster deal closures. 

With their deep product knowledge, AEs and SEs are better positioned to identify upsell and cross-sell opportunities, driving additional revenue from existing accounts. 

Furthermore, the improved communication between product and sales teams cultivates a collaborative culture, ensuring both teams work harmoniously toward shared objectives.