AI-Powered Sales: The New Norm for Businesses

Summary

In this blog, we will focus on the sales process in the age of AI and how we are already leveraging it.

We see AI as the next step to a complex algorithm we use to automate a task. The algorithm will get better and better over time.

The key takeaways are:

AI will result in more and better content for awareness generation.
AI will take over more of the activities of qualification and initial engagement.
Salespeople will get involved just in time (i.e. on-demand vs. scheduled meetings) to ensure continuity of conversation from an AI bot, escalated to a human team member.
AI and other technology components will increasingly result in specialized meeting platforms
Some repetitive tasks such as notetaking and CRM updates will be taken over by AI increasing data hygiene – streamlining the iteration and learning and driving to a close.

Ultimately a new breed of Customer Engagement Platforms will emerge to make sure all of these components work with each other seamlessly.

Through this blog we will also highlight some companies that we recommend that have offerings around AI integration.

Introduction

Chat GPT has taken us by a storm. We are already projecting the disappearance of marketing, the slashing of sales jobs, or even the need for CRMs. Hey, we may even eliminate purchasing, because we will have AI doing the selection and negotiation.

Here is my take. Most of the above will indeed happen, but eventually. And, unlike the “computers beating chess grandmasters soon” prediction, that took half a century to become reality, AI will thoroughly penetrate sales and marketing operations in under a decade. But not quite tomorrow.

We spent hours with various Gen-AI tools to build us a graphic of a chat-bot playing chess with a sales rep. While the end results approximates what we had in mind, we did not really want a person with six fingers. When it comes to a chat-bot conversing with a customer or prospects, we do not want six fingers in our answers. Just-in-time human intervention is crucial until AI is ready for prime time; and there will always be cases that have to be handled by a team member. We believe these shortfalls will be present in all aspects of the sales process that involve AI, making sales a team effort between the AE and AI. Hence, much of the use of AI will be in supporting its human counterparts, rather than replacing it.

1. Create Awareness – Get Noticed

Standard marketing activities to get noticed include:

Brand creation
Advertising
Publishing
In-person events, webinars, conferences
E-mail campaigns

In all reality outbound sales, e-mail campaigns, and cold calls are also about creating awareness. Since barely 1% of those activities result in a connection, these activities are better looked at as awareness generation.

The challenges are many:

Advertising efficacy is hard to measure.
Generating quality relevant content and publishing it in the right venues is hard.
In-person conferences and events are making a come-back and remain effective, but the explosion of online events makes it hard to get noticed.
E-mail campaigns and cold calls barely work, the number of touches necessary to get a prospect’s attention keeps going up.

How AI helps

One low hanging fruit area where AI has made its mark is content creation. We have seen with the rise of generative AI tools how easy content generation has become. Tools such as ChatGPT simplify writing while other image and video generation tools such as Midjourney have simplified branding and graphic design. Gone are the days where content iterations would take days. Teams are excuting faster with the help of tools that generate content in seconds.

The challenge? Generating meaningful content that stands out to an audience that is constantly bombarded with content - and more so now that content creation has become easier. The solution: Maybe quality over quantity?

2. Identify Intent - Qualify

As businesses have evolved, they now have multiple different products, distribution channels, payment plans, and hence, varied ideal customer profiles or personas. It has become challenging to identify a lead and qualify. Finding intent is like finding a needle in a haystack. The core challenge today is knowing when to put sales effort on a prospect.

How AI helps

Companies like 6Sense, ZoomInfo, Clearbit, Apollo are already employing AI-like complex algorithms to create “qualified” leads from overall behavior. Similarly, chatbots are evolving to determine intent based on the quality of the responses. Currently most chatbots are hierarchical, i.e. they have a set flow based on inputs from a visitor. AI Bots are capable of answering open questions on the data they have been trained - like product capabilities. In time, they’ll also be able to look up real-time data - such as product availability.

3. AI | AE handoff

I am certain there have been several instances when there was a qualified and engaged prospect on the website waiting to speak with someone, while an SDR was calling an unengaged lead. The result? Losing an engaged prospect and possibly irritating an unengaged lead. I strongly believe this part of the sales cycle will be the most crucial since it involves the hand-off from AI to AE.

How AI helps

The most frustrating part of a chatbot is that it is unable to take a prospect from start to finish every time. There comes a point where it requires support from the sales or service team. Providing an on-demand meeting rather than scheduling an interaction for some point in the future is what will become standard practice. The role of the AI therefore is to warm up the prospect, collect relevant information, and escalate the prospect to the AE when the prospect is ready.

On-demand meetings solve the customer’s direct pain point – I know enough about the product, but is it right for me? They also solve the business’ problem – I want my SDR or AE to focus on qualified prospects that are interested in my services. Optimizing their time and effort is essential.

4. Meet – Drive Opportunity to Decision

Once in a meeting, we want the AE (or the Customer Success Agent) to focus on the prospect, have call context, and meeting goals. The last thing we want is the prospect/customer to start the conversation from the beginning and the AE to scramble for information.

The right customer engagement platform makes the handoff seamless, and allows the AE/Agent to focus on closing the deal or resolving the issue.

How AI Helps

Today, AEs are expected to prepare for meetings. Meeting platforms such as zoom or google are focused on generic conversations and do not necessarily enable customer engagement.

Future customer engagement platforms will not only bring the customer and AE into the meeting but the CRM, AI, and all essential tech stack components. With an open architecture they’ll enable any solution component to become a “card” that can be added to a conversation.

AI will generate meeting goals dynamically, may leverage companies like Clearbit for additional information about a qualified prospect’s buy intent, suggest follow-up meetings or bring other team members into the conversation.

5 - Learn and Iterate

Even in the future not all sales will be closed with one meeting. CRM hygiene, learning, documentation will always remain areas for improvement. AI will take care of repetitive and non-intuitive tasks.

The challenge moving forward will be where SDRs will be required to take on more on-demand meetings. Companies will start to differentiate based on their conversation and their time to conversion.

How AI Helps

AI based note-taking platforms such as Chorus, Gong, Fathom are on the rise. They not only take record of the literal conversation, but also give detailed summaries of the key action items discussed during the conversation.

In time their accuracy will improve.

Conclusion

The need of the hour is to understand how far AI is ready to take a conversation today and move that goal post tomorrow. Either way the need for people in the conversations will remain. It is also fair to say that the team members carrying those conversation will need to increasingly be of higher skill and experience.

As solution components evolve rapidly, one key challenge to companies will be future-proofing their tech investments. Customer engagement platforms with embedded components, existing integrations, and open architectures to easily add/remove tech-stack elements will be crucial in assisting the evolution.

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