We posted a few weeks ago about the idea that Gen AI is the great equalizer and used the idea of the old TV show and more recent movies starring Denzel Washington. In his book “Co Intelligence: Living and Working with AI,” Ethan Mollick talks about how AI has the biggest impact on the poorest or average performers. "In study after study the people who get the biggest boost from AI are those with the lowest initial ability - it turns poor performers into good performers."
Well, that sounds plausible and great and all that – but where’s the use case in B2B sales & marketing. Well, there’s a few, and one example is the dreaded account planning mission. That’s when you all get together and identify, discuss and plan several target accounts that, for whatever reason, you feel like you should be doing business with. This is a great use case for a specialized GenAI (like Shadow). How so, I hear you ask.
Lets quickly run through the shortcomings of the generally used current process, accepting that even using the various information tools available, it remains a real drag.
1. Inefficient Use of Time and Resources
Excessive Time Spent on Research: While understanding your target account is important, spending too much time gathering information is a huge time suck…and it’s BORING. It slows down the sales cycle and ultimately reduces the number of prospects you can engage with.
High Cost of Customization: Crafting highly tailored messages for each target account is also resource-intensive and highly debated. This can be particularly costly for small to mid-sized companies with a limited marketing and sales bandwidth.
It’s a task that is too often assigned to opposite ends of the capability and cost spectrum – e.g. junior reps and junior marketing people on the one hand (but they’re cheap!), people sitting offshore with nothing else to do (and they’re cheaper!) and senior sellers at the other end of the spectrum.
2. Assumptions and Misalignment
Assuming Needs and Priorities: Even with thorough research, there is a risk of misinterpreting or overestimating the importance of certain needs and priorities of the target account. We’re all victims of bias, being overly influenced by mistaken assumptions - e.g. “Company X buys Sitecore services from us, so now we offer Salesforce services they should buy those from us as well!”
Only we know our customers – the misplaced confidence that only you know best.
We’ve got our ICP: (a personal favorite.) You’ve analyzed your customers and think you’ve identified the reason they did business with you. Notwithstanding the obvious, (like “we only sell blue cars, so we only want to sell to people who want blue cars!”), the assumptions are too broad. ICP’s are slanted towards you (often subconsciously) – that’s the antithesis of being customer centric and obsessed with personalization.
3. Scalability Issues
Difficulty Scaling Personalization: As your target list grows, maintaining a high level of personalization becomes increasingly difficult. This can lead to inconsistent messaging quality and effectiveness. What happens is that the closer you get to the end of the list the more you’ll see repetition in the messaging.
Resource Strain: Over-reliance on personalized messaging for each account strains your sales and marketing teams, potentially leading to burnout and reduced overall performance. Once more boredom rears its ugly head.
4. Delayed Engagement
Slow to Market: The time taken to gather information and craft personalized messages delays your engagement with potential customers. In fast-moving markets, this can result in missed opportunities.
5. Overcomplication and Lack of Focus
Complex Messaging: Crafting overly detailed and complex messages can dilute your core value proposition. Clear, concise, and compelling messaging often resonates more effectively. But you have to find the balance – we live in the era of increasing personalization and doing it at “scale” is something of an oxy-moron.
Alternative Approach: Finding the Balance
Most of these intentions and ideas of what target account planning is about and how it's done are valid - they just take too long, cost too much and are fraught with assumptions and biases. Why wouldn’t you use AI tools to gather insights, automate parts of the research, help craft the messaging, and combine it all together? This helps streamline efforts and ensure more timely, relevant engagement with prospects. Go back to the original thesis – GenAI is an equalizer. Used properly, it gives small and mid-sized companies the intellectual horsepower and time bandwidth of larger companies. How so?
Time – (is money). Its hard to get a statistically valid estimate of the amount of time companies spend doing this, and as we all know anyway, there are three types of a lies – “lies, damn lies and statistics.” Anecdotally, and based on my own experience, we spend hours on this across multiple people (per account). Even with resources sitting offshore, using GenAI will still save you time, money and produce better, unbiased results.
Boredom – most of this type of work is a real drag. The uncomfortable truth is people don’t like it, and as the time goes by the quality of their work declines. The explosion in internet information has actually made it worse, ‘cos there’s so much information out there, and God forbid we miss something.
Bias - Teams will sit around and identify their USP's (biased), then make superficial connections between those and the target companies. A well tuned, specialist AI is incapable of those types of biases. It'll tell you where the synergies really exist between your two organizations, and they're probably not where you think they are!
And now the hanging pitch:
Can’t I just use Chat GPT? – Chat GPT can neither get to the detail of the target company nor can it match those details up to your most contextually relevant USP’s. A specialized Gen AI (which is correctly tuned) can.
A specialized Gen AI (which is correctly tuned) is also totally objective. It might not tell you what you want to hear, but as Denzel Washington says in another one of his movies (Man on Fire), in this context GenAI is like a bullet “and a bullet always tells the truth.”
