Selling with Data #91 - Unlocking AI with automated seller activity

It is widely accepted that teams using data and analytics outperform teams that do not. You would think when it comes to sales team using data and AI to improve outcomes that it would be a no brainer, but that isn't often the case.

Five years ago, the best run sales teams in the industry invested in sales enablement tools to capture seller activities and convert the data into insights and a better understanding of their operations. Sellers logged all their activities manually, and over time the technology improved to automatically log messages and meetings into the CRM system. Leading sales teams have been doing this for over 5 years!

“Sales activity tracking historically has been about administration: tracking emails, meetings, notes, and other customer interactions that helps managers and sales leaders alike understand the depth to which their reps are engaging with their customers and coach to best practices,” - Matt Haller, Sales Ops Expert at LinkedIn.

Part of the unspoken employment contract for nearly every modern enterprise company is that sellers log their activities to drive data based decisions and inputs to performance management. It isn't optional, it is the way sales teams operate.

Sales teams who continue to debate if they should track seller and technical seller activities are like professional sports coaches who question if they should watch game film. If coaches don’t know what their players are doing, they can’t spot patterns, correct mistakes, or double down on what works. They are coaching blind.

Now, there is yet another important benefit to the sales tracking: Artificial Intelligence (AI). AI enables insights and automation to drive productivity, but those benefits require the baseline of accurate sales data.

“With the advent of Generative AI, we are increasingly seeing companies leverage their internal data to give reps ‘next best actions’ and other selling guidance that frees reps to spend more time with customers. And just like building a house, the weaker your sales data foundation, the less effective your GAI efforts will be." Matt Haller, Sales Ops Expert at LinkedIn

To continue to stay ahead in sales, you need AI to drive competitive advantage. To leverage AI, you need data and automated activity collection. Without good data, you cannot fully use AI.

A challenge is that when reps hear tracking sales activity, they often assume that means they have to spend hours manually updating their CRM system. Now, however, there are tools that automate activities from Outlook and other sources directly into the CRM system – taking the burden off the seller. The seller turns on the service and activities are logged to the right contact and account like magic.

CRM system like Salesforce can track sales activity through an add-on data capture tool or, if there are specific concerns, from manual capture. Tools easily connect to a seller’s inbox and calendar adding contacts, meetings, and emails automatically into the right contact or account in the CRM system.

Examples of how sales applications are leveraging AI to help sales teams.

• By analyzing large sets of data, AI algorithms can quickly identify patterns and characteristics of ideal customers to make the prospecting process more accurate and less time-consuming.
• Gong, Chorus, Salesloft, and Seismic analyze calls in their own platform, so sellers and sales leaders can listen to recordings and track call data. They can also write that data back to Salesforce. This is really helpful in identifying trends across meetings and for coaching opportunities.
• AI can perform repetitive and administrative tasks, such as scheduling meetings, sending follow-up emails, and updating CRM systems – freeing up sellers for strategic activities, like meeting with clients and partners.
• Forecasting tools like Clari and Envisio have add-ons for sales data capture as well. Capturing sales activity to use in forecasting can be a useful way to minimize manual data entry and drive more accurate forecasts enriched with non-traditional data sources.
• This one seems a little extreme to me. Skynamo helps sales managers keep track of representatives who spend a considerable amount of time outside the office pursuing leads. It offers a GPS feature that shows each sales representative's location in real-time and automatically generates relevant statistics, like how much time they spend with each client.

No matter the usage, the first step is addressing the cultural concern of sales activity tracking. The primary objective isn't for monitoring purposes, it is to quickly and accurately collect what is working and not is working – then to scale those insights to drive greater impact. This lets sales leaders act like professional coaches and watch game tape.

Sellers who report on their sales activity see how they're doing compared to their peers. They can use that data to identify areas of opportunity an if they are having the right engagement in their territory. Sales activity also gives a quantifiable data point to show effort, which should be an input into seller performance management and recognition.

Sellers and sales leaders who consistently do all the right things have no issues with automated sales activity logging. On the other hand, the louder the objection the more likely illuminating a deeper problem about low activity. Of course, there are legitimate reasons to filter some messages or meetings, which is why there are manual and automated ways to log messages and meetings into CRM systems.

“The most impactful way I've seen of getting people to fill out the data you need is to prove out the value first. Once they see what is possible with the data they will want the insights for themselves and do the work to make sure everything is tracked properly. When they know the data is being used and adds significant value to their day-to-day life it won't seem like menial paperwork” - Tom Yeager, Revenue GTM Analytics Lead

I recently heard about a conversation between a first and second line manager about one of their sellers. The first line manager complained that the sales reps was lazy and questioned if they were going to succeed. The second line manager looked at the seller’s activity data and saw that the seller was one of the hardest workers on the team but most of their messages were not converting because the messages were not well written. By having the activity data, the leaders knew where to coach the seller, in this case how to use generative AI to create more concise and effective messages, changing the trajectory of the conversation and helping the seller reach their potential.

What are you doing to automate seller activity data and to use it with AI to drive better outcomes?

Good selling.