Three ways you can start using AI in RevOps today

New Year, New You, Unlimited Possibilities (with AI!)

No, this isn’t an article about New Year’s resolutions, instead it’s an article to talk about what you should be thinking about in terms of AI and go-to-market (GTM) as we kick off 2024!  I’m working with a team, and we’ve mapped out 65 critical capabilities across all areas of GTM and assessed them in terms of the level of automation that can be achieved through AI as well as transformational impact that AI can have on them.  We will start publishing this research soon to share high priority areas and ideas to help you start transforming your organization.

The number of new startups focused on GTM (and on RevOps in particular) is incredible right now.  Each week I talk to another company that’s attacking a problem that has traditionally challenged most organizations.  New AI capabilities are driving real innovation in sales enablement, territory creation, data cleansing, tech stack automation, agent-based selling, forecasting, language translation, messaging architecture and so much more.  Over the next few weeks, I’m going to highlight a couple of these and talk about the changes I’ve been seeing that get me really excited about where RevOps and AI is going this year.

To kick off the year let’s talk about three examples that I’m seeing that I think a lot of RevOps teams should consider for this year. 

#1: Improving Sales Hygiene Through AI and Automation

One of the biggest challenges that I’ve always faced is getting my sales teams to keep their data up to date.  My personally philosophy is – if it’s not in salesforce – it doesn’t exist.  The best use case in this area that I’m seeing these days goes something like this:

• Sales Executive has a zoom meeting with a prospect and the transcript is saved in their sales tech infrastructure (in zoom, gong, etc.)

• Analysis of the call transcript (either from ChatGPT or Claude) happens automatically as soon as the call ends and provides an overall summary, sentiment analysis, action items and key next steps

• The transcript and summary is automatically uploaded into salesforce into the right record

• Post-call action items are automatically loaded into salesforce

• Next steps with due dates [blank if not identified] are automatically put into salesforce

• Email with a link to review all of this content is automatically sent to the sales executive (with prompts to fill in any missing pieces of data)

All of this can be relatively easily done today with no-code/low-code tools (e.g. Zapier) with minimal changes to existing sales workflows but with a big improvement in hygiene with solid follow-on information.

#2: Consolidation of Survey Results (or Feedback):

This is something I’ve personally been doing for several months – taking large collections of data from survey results and getting instant categorizations, themes, keywords and summaries.  I’ve personally found that Claude gives me the best results (by far) when doing this kind of work.  I’ve tried ChatGPT (4.0), CoPilot, Bard, Claude and Perplexity and for me – Claude wins hands down every time.

I was recently working with one of my clients and we were analyzing user-testing feedback for a new product.  We had tons of raw feedback (text) in three major categories.  One of the benefits of using Claude is there is an extremely large context (input) window – it can accept about 500 pages of text – so there was of us in this case having too much data from a single survey.  Here’s the prompt I used:

I'm uploading product feedback from some end user testing results. There are three sections in here. Can you give me a detailed summary of the key issues and findings from each section and give me a list of the most commonly found keywords in each section as well. After summarizing each of the three sections provide a final overview summary and key issues found that cut across the document.

I got exactly the type of summary I wanted. I ran the same query in ChatGPT just to compare, and while ChatGPT is amazing at a lot of things – the summary from Claude was 100x better.  I’ve found that to be generally true whenever I ask for transcript summaries, next steps, and action items from lengthy documents. This was perfect feedback for the product development team needed, and it was in an easily digestible format.

#3: Improving The Messaging in Your Presentations and Training Content

How good is the messaging in your presentations?  Do the headlines and content really convey what you want them to? Figuring this out can be a challenge – but the new vision capabilities in ChatGPT can really help.  Companies have tons and tons of data, but it’s often buried in hard to use formats (PowerPoint slides!).  ChatGPT can now analyze presentations in ways that even a few months ago would have seemed impossible.    

I’ve often found that salespeople don’t often stick to the “approved” corporate presentations that the marketing or sales enablement teams make and tweak them and/or use older content that they are familiar with.  Want to find out where your messaging is working and not working?  Gab a handful of presentations that your sales team is actively using today – and with ChatGPT it is easy to do the following kinds of things:

• Compare multiple presentations to find what’s common in them and what is different in them (does your best salesperson have something others are missing?)

• Compare a salesperson’s presentation with an official corporate presentation to see if key elements are missing (do they have year old architecture drawings or lists of features that are no longer supported?)

• Ask ChatGPT which of the presentations has the most compelling content and the best visuals (this often takes multiple prompts and requires that you give it very specific guidance – but the results when done right can be amazing)

• Ask ChatGPT for specific ways to improve the presentation and messaging (“Please analyze each slide in this deck and make one recommendation per page to make the content crisper or more appealing”)

ChatGPT can analyze each slide in the presentation (both the text and visuals) and respond to those types of detailed questions.

Another important way to look at the messaging is to upload a large number of meeting transcripts and ask your favorite AI tool to compare them to a document that has the key messaging in it.  “Analyze these 15 sales meeting transcripts and compare each of them to the five critical talking points in document X and give me an assessment of how many of those are being covered in each meeting.” Assess how well teams are incorporating key messages, which ones are most often missing, and if anything is being incorrectly stated so that you can make changes to your training. 

Wrapping Up:

There is so much innovation happening right now.  This week at CES we’re starting to see cool new products like the rabbit r1 (rabbit — keynote) and the Samsung Ballie (https://x.com/LinusEkenstam/status/1744708363370295776?s=20).  We saw BLAND.AI launch the fastest conversational AI ever (

https://twitter.com/usebland/status/1743411488612913429?s=10&t=cqRrOAeItfq6MsNwv2NGEA), and OpenAI announced that the GPT Store will launch next week.

There isn’t a part of the GTM organization that won’t be impacted by AI, and this is going to be a great year to see companies do incredibly innovative things.

As always, ending with a photo of Ollie – and one of his brothers (Sully).  We got them together for a little playdate during the holidays.  Always great to have two large Saint Bernards trouncing through a park!

Best,

Steve

steve@revopz.net