Walking the talk with AI
19th September 2024 | Bob Apollo
How can you harness AI to have better sales conversations?
Most independent observers would agree that Artificial Intelligence is unlikely to completely replace skilled and experienced businessto- business salespeople in complex buying environments any time soon. But it is also clear that AI is already capable of enabling skilled and experienced B2B salespeople to become even more effective.
Salespeople who have embraced the potential for AI-enabling sales conversations are generating three times as many advances as their less effective colleagues, leading to shorter sales cycles and higher win rates.
The more forward-thinking of my clients are already seeing the impact that effective use of AI can have on sales conversations: some are reporting that salespeople who have embraced the potential for AI-enabling sales conversations are generating three times as many advances as their less effective colleagues, leading to shorter sales cycles and higher win rates.
AI is also enabling salespeople to more effectively qualify potential sales opportunities, and to recognise and disqualify those deals that they are never likely to win far earlier in the sales cycle than they would otherwise be able to – freeing up their time to find and win more of the right sort of prospects.
This isn’t just about doing more of the right things more effectively: it’s also about anticipating, avoiding and eliminating predictable sources of error in the sales process, such as recognising and addressing gaps in our knowledge, and making sure that we take the right actions and avoid the wrong ones.
In this article, I want to focus specifically on the application of AI to improving the quality (and therefore the outcomes) of sales conversations in complex B2B sales situations, in which a series of interactions have to be successfully navigated and mastered if we are to win the customer’s trust.
AI for research and preparation
The first obvious application lies in pre-call research. Experience tells us that the better prepared salespeople are, the more likely they are to have a successful conversation – one that improves each of the parties’ knowledge and either advances both the buying and selling journeys or disqualifies the “opportunity”.
Some of the most obvious sources include annual reports, company websites and LinkedIn profiles. We need to look for the organisation’s key priorities, latest news and current initiatives, and relate them to our own value proposition and how we can help them achieve their desired business outcomes.
Understanding the organisation’s technology platform can not only help us to work out where our offerings could fit into their environment – including established “competitors” – but also enable us to deduce their attitude to technology acquisition and where they might typically fit on the adoption curve. For example, do they always buy from established market leaders, or are they willing to buy emerging best-of-breed solutions?
At the individual level, LinkedIn and other businessoriented social media profiles are the most obvious source. We need to go beyond the obvious aspects of role, responsibilities and career trajectory and try to understand what they are driven and motivated by. For example, what articles have they written, commented on or liked, and how can we make the connection with how we might be able to help them?
AI tools can of course help us with this research, but they can also help us to prepare to have a value-creating conversation that leaves our intended audience thinking that the interaction was a valuable use of their time. The key to getting the most out of tools like ChatGPT lies in the quality of our prompts: the more detailed and relevant the prompts, the more useful the outputs.
This shouldn’t be left to each salesperson to work out for themselves; sales teams must collaborate on the most effective ways of providing useful guidance (as well as, for, example, sharing the stories and anecdotes most likely to be relevant to each type of prospect, which are unlikely to be unearthed by external AI tools). But no matter what AI suggests, each salesperson must always apply their own experience and judgement.
AI for analysis and follow up
AI can also play a very powerful role in recording, analysing, interpreting and summarising each conversation. Of course, this requires that the conversation is recorded, but in my experience if we position the purpose of the recording as helping to ensure we don’t miss anything important and can follow-up on any customer requests most effectively, getting the customer’s agreement is rarely a problem. And we don’t have to restrict ourselves to web-based interactions: some AI recording tools can be used just like a phone-based voice recorder in face-toface meetings.
These AI-enabled call recording and analysis programs have evolved rapidly from the first generation of not-alwaysvery- accurate transcription tools to fully functional systems that not only transcribe every conversation with increasingly impressive accuracy, but also create summaries, action lists and – perhaps most powerful of all – assess the sentiment of the conversation as well as analysing how well the organisation’s selling methodology has been applied.
The speed with which the most advanced AI tools have evolved is breathtaking. There is already a material gap between AI-enabled salespeople and sales organisations and those that have been holding back – and that gap will soon become a chasm.
These last two elements – sentiment analysis and methodology scorecards – have the potential to be huge gamechangers, not just for each salesperson’s professional selfawareness and effectiveness, but also for sales managers when prioritising where their coaching energies should be focused.
The more advanced AI-powered sentiment analysis tools are already able to fairly accurately judge the mood of the meeting, and the level of participant engagement – and they will get better. This is not a substitute for the salesperson’s judgement, but a highly useful complement. As this type of analysis evolves, we can expect it to become even better at spotting things that the salesperson may have missed or undervalued.
AI-powered methodology scorecards can already assess how well the sales organisation’s defined sales processes and methodologies have actually been applied in each prospect conversation. For example, these tools can identify how well qualified the opportunity appears to be on the basis of the information provided by the prospect and evaluate how well the salesperson has executed on the key best practices of their sales organisation’s defined sales process.
But all of this is just scratching the surface of what will soon be possible. The speed with which the most advanced AI tools have evolved is breathtaking. There is already a material gap between AI-enabled salespeople and sales organisations and those that have been holding back – and that gap will soon become a chasm.
Let’s be clear: AI will not replace experienced, empathetic salespeople in complex B2B sales environments anytime soon. But it will enable those salespeople (and the organisations they work for) to outperform their laggard/Luddite peers by even greater margins.
AI as a coaching tool
The latest generation of AI-powered conversational intelligence platforms are already offering invaluable insights to self-aware salespeople. But if they are to be widely adopted, it’s critically important that they are positioned not as corporate-imposed spyware but as powerful self-coaching tools.
In addition, of course, these tools can also help each salesperson’s manager to analyse more conversations more effectively, and to quickly work out where their coaching could have the highest possible impact, benefiting both the salesperson and the manager.
All-in-all, my experiences have convinced me that AI will make an increasingly important contribution to raising the quality of B2B sales conversations: benefiting the salesperson, the organisation they work for, and their prospective customers.