Less Paperwork, More Productivity: Tech Sales With AI

Technical sales pros have this in common: they enjoy customer interactions.

But technical sales do not happen in a void. We need our organization to provide us with excellent products and services so that we can design innovative solutions.

Because of the nature of our work, we have a wealth of information to offer other departments so they can optimize their work.

Product Management relies on us to identify market trends. Support and Customer Success need to know account history to perform their tasks effectively. The C-suite uses the intel we gather from the trenches to set strategy.

However, this critical responsibility is also a source of constant struggle. Complaints about sales opportunities needing more documentation are a recurring theme in many organizations.

Could AI help make technical sellers and engineers more effective by lowering the time spent capturing and disseminating information vital to the organization? Absolutely.

Making Sense Of Chaotic Data Sources

Executives understand the value of the data captured by salespeople and sales engineers. They have developed policies to ensure that this data is saved somewhere where it can be accessed by stakeholders.

This can take multiple forms. I have seen compensation partially linked to the upkeep of opportunity information in the CRM and lengthy preparation documents that sales teams have to put together prior to important meetings.

And yet, people keep complaining that the information is incomplete. Why?

One reason is that multiple sources of mostly unstructured information are usually spread across various systems. The CRM would contain some of that information, but so would the emails exchanged with clients, minutes from external and internal meetings, and so on.

Trying to order through sheer discipline so that all the information goes through one single source of truth has proven to be difficult because each of these systems is uniquely suited to certain tasks.

Besides, organizations are facing a tough Faustian bargain. Paying tech salespeople to centralize all info in a central location - and maintain it over the whole sales cycle - comes at a high cost. More time on paperwork, no matter how useful it is, means less time spent selling and solutioning.

However, not enforcing discipline can lead to mishaps, chaos, and endless post-sales meetings because of the need to synchronize.

AI can help break the logjam. This technology excels precisely at making sense of unstructured data. It can analyze several reports, emails, and meeting minutes and generate recaps and reports, saving the technical sales teams precious time.

Because AI is so good at making sense of unstructured data, some information capture rules can be relaxed. Focusing on what data gets captured and which details should be saved rather than how and where it needs to be can enhance the productivity of team members.

AI To Prevent Meetingitist

At some point, AEs, SEs, and FEs must turn over accounts and projects to Support, Project Management, and Customer Success. Once a deal is closed, their main duty should be to close the next one.

Often, this process does not happen very efficiently.

Sometimes, other stakeholders cannot do much for the client without the Presales' group active support. Albeit it may be by design, as many solution departments carry delivery responsibilities, at other times, it leads to what can be described as "support creep."

This happens when your SEs and FEs get involved in lengthy internal and external meetings to help other departments deliver the solution because they need more information to do their work.

Alternatively, the customer may choose to contact the sales engineer directly to get answers to their questions and forgo Support altogether.

In both cases, it comes at a heavy cost. It means that your organization will have less time to do presales. I also found that this "creep" may not only grow with revenue but sometimes faster than revenue.

Obviously, it is not sustainable.

AI can help here by making it easy to generate recaps of customer situations on the fly and enabling groups like Support to use tools that let them search documentation effectively.

But I would go a step further. AI relies on information captured elsewhere than your engineers' heads to leverage it. Could we one day imagine that AI could analyze how complete the field reports are and gently nudge engineers into providing missing information?

Now, this would be of tremendous help. I found that most people are more than willing to ensure the information is captured but may sometimes forget even the obvious missing pieces. Blame it on being in the middle of the action. Having an assistant reminding you - and even helping you - to capture the information would be just what the doctor ordered.

Better Customer Insights For A More Effective Corporate Strategy

We should not forget about two other stakeholders who rely on the Technical Sales and Presales group for information: Product Management and the C-Suite.

Their needs are similar: establishing a strategy to be more successful tomorrow than today. But they cannot do so effectively without learning what has been working well - and not so well - in the current business.

The same ability of AI to quickly generate recaps out of tons of information is obviously helpful.

But it goes further. LLMs have become the most popular front end of AI, but the strength of the technology also resides in finding patterns while sifting through reams of data. After all, this is how these LLM models get trained in the first place.

Finding patterns in quantitative data such as financial statements and quotations can definitely provide important insights into the health of the business and some of the opportunities that could be tapped through smart strategies.

However, more qualitative data may be used to establish some useful metrics. Consider gauging client satisfaction based on communication with clients and cross-checking that information with products sold, number of visits, location, industry, and more.

Ultimately, AI may become "smart enough" to suggest relevant patterns without being provided with prescriptive prompts.

All of this will, of course, affect more departments than just Sales and Sales Engineering. But as purveyors of critical information, both of these departments will need to be playing an important role for these benefits to materialize.