Future of Sales and AI

Is sales going to be safe from the AI bots and algorithms?

Let me cut to the chase, your job is safe. Whether you are a sales rep, manager, ops, or enablement person, AI is not becoming sentient anytime soon to take your place.

However the quality of AI has significantly improved over the past few years, to the point that it is delivering real business results. It is also fueling a renaissance in the sales technology world, with numerous startups racing to offer up innovate solutions for sales teams.

I was invited by my friends at MindTickle to join them for a conversation about the impact of AI and the world of sales and sales enablement. The talk is today during the FUTURE OF SALES FESTIVAL hosted by the Sales Enablement Collective.

If you read this email in time, you can catch the talk here at 12:30 PM EDT / 5:30 PM BST. In preparation for the talk, I wrote my thoughts below about what I see as the state of AI in sales and sales enablement.

Even if you think that this topic does not matter to you today or in the future, it is important to stay on top of the trends. The early adopters of CRM saw huge upside in revenue attainment and close rates. Those the jumped into prospecting tools early significantly boosted their lead conversion and pipeline generation. The technology is not a replacement for hard work and intelligence, but it can accelerate the good work you are already doing and scale it up.

In that respect, AI has the potential to create a tidal shift in how teams operate and perform. The winning sales teams will meld solid process, smart hiring practices, and AI tools to outperform their competition, and it will be lights out for those teams that do not get wise to the value of AI enabled technologies.

May you enjoy what I have to share this week in the essay below and catch you next week at the Enterprise Sales Forum. And please share with your colleagues 😉

1) Let’s level set at the start, can you define AI and what it means from a vendor standpoint and a customer standpoint?

AI is simply a way of allowing computers to make complex decisions that normally would require a person. For example, driving a car, offering up personalized product recommendations, or in a sales context, choosing which customer to call next. For AI to do these things, it often requires something you hear called machine learning (ML), which is the process of taking large amounts of data to create and validate logic that enables AI to make intelligent decisions.

While AI has enormous potential, it can also be a buzzword with little value. At Amazon, we avoid this by working backwards from the customer. We ask what real business problems are we solving for customers which involve lots of data where meaningful insights or outcomes can be created for customers. This results in services that allow our customers to use services that are readily available and deliver value faster.

2) AI has played a critical role in helping teams at companies large and small to scale, how have you seen AI help scale sales enablement and readiness programs?

Sales is awash in unstructured data. That is any data that is free text, like the notes you put into your CRM, emails, call recordings, sales contracts, social media activity, and opportunity / accounts plans. That is a ton of data, which is a perfect use case for using AI. We already see it today with sales tech companies recording and analyzing sales calls in real time, surfacing up insights from social media to suggest leads and contacts to reach out to, or crafting responses in response to customer emails. As this data is collected and rolled up, it provides guidance in terms of what is working and not working for the sales team, helping to raise team performance.

There is also a ton of value in structured data, the data that are discrete fields in a CRM for example. Forecasting is a huge opportunity area in the sales tools market, mining all the data in CRM and other sources to build a much more accurate assessment of pipeline and forecast health than can be done by people.

3) In the long term, do you see AI as replacing members of a sales enablement team or do you see AI more as supplementing it?

AI is not replacing humans in sales. Rather, AI is enhancing the work of sales and sales enablement by removing a lot of the undifferentiated heavy lifting that most teams do today. Instead of sifting through ungodly amounts of data, fixing it, transforming it, and then going through the tedious effort to extract meaningful insights from data, sales enablement can use ML tools that are doing a lot of the data cleaning, transforming, and processing to surface insights much faster. AI in that sense is a value creator for uplifting the profession to be more strategic in creating value for sales teams and delivering results faster. This will enable sales ops and enablement professionals to level up their own skills as data analysts to become what I called revenue scientists.

4) What is the relationship between AI and Automation? Can AI automate some of the more mundane and time-consuming tasks to help accelerate the launch of enablement programs?

It is important to note that Automation and AI are different things. Automation is operationalizing a manual and repeatable process so as to remove excess work. Integrating an email server to CRM and tying emails to contacts and accounts is automation. Another example is prospecting platforms that send emails in sequences or dialing leads in rapid succession.

AI is about making decisions which require insight. This could lead to automation, but does not necessarily have to. The real power of AI is that it can take a lot of data and “see” things that humans would not be able to, even if given a lot of time to do so.

AI generated insights can allow sales enablement teams to explore processes that could be automated. For example, the propensity for a customer to churn can be derived from ML and AI can launch an automated “churn campaign” for an account manager. Another idea would be to build a call list of the best leads for a sales rep to contact based on social media sentiment.

5) Can AI help sales leaders with coaching their reps or promoting a culture of coaching?

Coaching does not happen nearly as often as it should because it is a massive time suck. Very few enjoy it, and those managers that commit to being “coaches” often struggle to do it in a way that is impactful. But let’s remember, by some studies, sales reps receiving at least three hours of coaching per month exceed sales goals by 7%, increase revenue by 25% and lift close rates by 70%. Coaching is a worthwhile investment!

AI accelerates the delivery of coaching. Already teams using call intelligence tools are seeing significant sales performance improvements. Before managers would have to sit through a limited number of calls, and the insights from those experiences were scattershot and highly variable. By recording calls, analyzing calls, and sending feedback in real time, reps and managers are getting instant feedback that can be used for data-driven coaching, something that has not existed in sales prior to these technologies.


6) The impact of data gathering and sharing is a key aspect of how AI works, so how do you see the role of data and AI's use of data in sales enablement programs?

Data is the lifeblood of AI. AI leverages machine learning, which derives insights from massive data sets. The next evolution of sales enablement is becoming more data savvy. The most successful of sales enablement practitioners are very comfortable with data tools like Tableau, Looker, and Amazon QuickSight, they can dive into the data warehouses, some are even conversant with light scripting and SQL. Sales enablement professionals are going to be the revenue scientists of sales teams and organizations.

It should also be noted that data science, machine learning, and AI are hard skills to master. There will be a wide talent gap, so this is where sales technology providers can help. On the AWS side, we provide ready-made AI services that companies can plug into their tools or sales stacks into so as to leverage AI for specific use cases. Some these services include:

  • Amazon Forecast which analyzes historical time series data to generate accurate sales forecasts

  • Amazon Lex for AI Chatbots creates sophisticated conversational interfaces for any app using voice and text

  • Amazon Personalize creates custom recommendations for customers, boosting engagement and add-on sales

  • Amazon Comprehend finds insights and relationships in text from unstructured data, useful for analyzing customer emails, sales calls, social media streams, etc.

7) How do you see AI potentially impacting sales enablement in the near future?

The sales stack is continuously changing. The advancements we have seen in the sales technology market over the past decade will only accelerate as companies add AI/ML to their stacks. This will not just cover general sales workflow and the use cases mentioned earlier, but also industry specific use cases and diving deeper into augmenting sales performance.

The other fascinating possibility is the aggregation of sales performance data to finally derive genuine insights into what impacts sales results. Much of the sales industry up until now has relied on surveys and self-reporting to derive these insights. Now that large amounts of data are being collected, we are already seeing some interesting initial insights into prospecting tactics, cold calling, sales process, etc.

Lastly, AI will combine with innovations in the VR/AR to create realistic sales training. We can finally move on from cringe invoking and thoroughly ineffective live sales role plays. Instead, in the metaverse, salespeople will interact with customer simulations that engage and react in real-time to sales rep prompts, providing an authentic and safe sales coaching experience.

Mark Birch, Founder of Enterprise Sales Forum

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