Almost Timely News: ??? Transformative Strategy with Generative AI, Part 3 - Competitive Analysis (2025-03-23)
Almost Timely News: ??? Transformative Strategy with Generative AI, Part 3 - Competitive Analysis (2025-03-23) :: View in Browser
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What's On My Mind: Transformative Strategy with Generative AI, Part 3 - Competitive Analysis
I just typed the notes heading in my notebook for this week’s newsletter, transformational AI and competitive strategy and somewhere, some consultant just yelled BINGO. That’s a lot of buzzwords in a sentence.
Last week we covered what transformation is (changing forms) so we won’t rehash that, save to say that if your competitive analysis process looks the same after applying AI to it, it’s an optimization, not a transformation.
Part 1: Why Competitive Analysis
What’s the point of competitive analysis? Many a business book has quoted various leaders as saying that your focus should be on making better products and services, and leave competitors to their own ways. The answer to this really depends on the kind of competitive environment you’re in. If you don’t have significant peer competitors, then competitive analysis is probably not a good use of a ton of resources.
If you do have a peer competitors - maybe you’re Samsung competing with Apple, or Lao Xiangji competing with KFC, then you very much want to do competitive analysis.
And all businesses should do it in some capacity, if for no other reason than to be aware of major shifts in the market - especially in what customers want.
This is the single biggest gap in most competitive analysis today. Most competitive analysis looks at what the companies are doing. That’s not the worst thing in the world, but it doesn’t directly help your business.
So what should you be paying attention to? Well, before we get to that, let’s review some basic competitive analysis frameworks.
Part 2: Competitive Analysis Frameworks
Dust off your B-school books, unless you’re like me and you sold them back to the school at the end of the academic year. Then pretend to dust them off. You probably learned three different competitive analysis frameworks:
SWOT Analysis
The favorite of business schools and consulting firms because it’s a beloved 2x2 matrix, a SWOT analysis looks at strengths, weaknesses, opportunities, and threats. However, almost everyone does this wrong. Nearly every SWOT analysis I’ve read mixes items up in the different categories, or worse, applies it at a larger scope than intended.
A SWOT analysis is not an industry analysis. Industry analysis doesn’t belong in it. A SWOT analysis is all about comparing you versus ONE other competitor.
The second major thing many, many people do wrong is mixing up items. The SWOT analysis is really a consulting 2x2 matrix, so there’s two axes. One axis is strengths and weaknesses, the other axis is you and your competitor. Here’s what I mean:
See it?
Your strengths are your competitor’s threats. Your threats are your competitor’s strengths.
Your weaknesses are your competitor’s opportunities. Your opportunities are your competitor’s weaknesses.
Once you understand this, making a crystal clear SWOT analysis becomes substantially easier.
“But what about…” is the usual objection, followed by a dozen different scenarios and what-ifs. Those typically don’t belong in a SWOT analysis. Where do they belong? Probably in a Porter’s 5 Forces.
Porter’s 5 Forces
Michael Porter’s 1979 5 Forces model, now just called Porter’s 5 Forces, are a big picture look at your industry overall. This is where most of the what-ifs and what-abouts fit.
The five forces are:
Porter’s 5 forces is a great place to talk about the macro picture of the industry, from startups that are more agile to customers making different purchasing choices.
The third framework cleans up the remaining what-ifs: PEST.
PEST Analysis
PEST is a 4 part framework to look at the biggest possible picture:
This mops up the remaining considerations that probably come up in strategy meetings.
Okay, but how does this help us do competitive analysis better?
There’s one more dimension we need to consider: the customer.
Part 3: Voice of the Customer
This is the missing ingredient in almost every competitive analysis. In many ways, we don’t care about what our competitors are doing, except as it helps us to understand what the customer wants and can get from our competitors that they can’t get from us.
The challenge for many of us is that voice of the customer is mostly a buzzword, something we give lip service to, but never really spend time on. Why? Because it’s so vast. It’s vast, it’s unstructured, it’s messy, and let’s face it: the axiom that the customer is always right is… flawed. Sometimes the customer’s just an idiot, like the guy demanding a pizza from the drive through line at a Wendy’s. Sir, this is a Wendy’s.
However, there can be CONSIDERABLE competitive advantage to be found in the voice of the customer. The trick is twofold: getting the data and processing the data.
That’s where media monitoring, deep research, social listening, and a host of other technologies can be super helpful. These tools can gather up huge amounts of unstructured data, which we can then feed to AI, to develop a voice of the customer.
There are 14 dimensions to the voice of the customer we could be using:
You’ll note that these are a mix of internal and external data sources. When it comes to competitive analysis, which is the point of this issue of the newsletter, we want to focus on external data sources so that we can do apples to apples comparisons of data.
Here’s why: the voice of the customer can be segmented into two parts: the voice of OUR customer, and the voice of our COMPETITOR’S customer.
Do you see it? Do you see the magic in re-thinking the voice of the customer this way? The customer isn’t an amorphous blob of opinion like a holiday jello fruit salad. We have different classes of customers, and at the broadest level, we have our customers, and our competitor has their customers.
Part 4: VOC/SWOT
Let’s get to the magic of this. If we can gather the voice of our customer, and we can gather the voice of our competitor’s customer, then we can use generative AI to process all that data (probably in batches for large datasets) and boil them down into four categories:
This is very clearly a SWOT analysis - what our customers like or don’t like about us is our strengths and weaknesses, but from the customer’s point of view, not ours. We can brag about what we think our strengths and weaknesses are, but those are not the opinions of the people paying the bills.
And in turn, what our competitor’s customers like and dislike about them are our threats and opportunities. If your competitor’s customers are all complaining about high prices, there’s an opportunity potentially to beat them on price.
Great. So we understand how things should work. How do we bring this to life? How do we, to fill up on buzzwords, transform our competitive analysis with generative AI?
Out of the 14 dimensions of the voice of the customer, we're going to use 2 of them in this example because this is just a demonstration, not a paid project. We'll use search intent data, which we can get from an SEO tool like AHREFS. And we'll use Deep Research, from three different Deep Research tools - Gemini Deep Research, Perplexity Deep Research, and Grok Deep Search. We'll be blending the deep research outputs together, as each one has its own strengthsn and weaknesses.
Once we have these pieces assembled, we can then prompt the generative AI tool of our choice to help us assemble the VOC/SWOT. For this analysis, I'll take the perspective of MarketingProfs, as though I worked for MarketingProfs. (I don't, but I speak frequently at their events)
Here's an example prompt which will work best with a reasoning model.
You're a management consulting expert in the style of McKinsey, Bain, and BCG. You know competitive analysis, competition, market dynamics, and competitive analysis frameworks like SWOT, Porter's 5 Forces, Competitive Matrix, PEST/PESTEL, and many others. Today we'll be assembling a SWOT analysis. Here are the rules you must follow and the desired outputs.
We will be performing a VOC/SWOT, a special type of SWOT analysis invented by the management consulting firm TrustInsights.ai.
The companies we are performing the analysis for are:
You will be given voice of the customer data for our client and their competitor in two formats:
From this data, you will synthesize and report aloud the following VOC Analysis:
Once you've reported aloud all four categories of data from the sources, you will then assemble the VOC/SWOT.
The VOC/SWOT is a SWOT analysis using voice of the customer data. You'll build a SWOT analysis with these categories:
Produce the VOC/SWOT after you have produced the VOC Analysis.
Now, once you've got this analysis, this is only the starting point. As with any SWOT analysis, it's what you do with it afterwards that really matters. What decisions will you make? What actions will you take? How will you overcome your weaknesses and double down on your strengths?
And it's not a great leap of imagination to take the same dataset for multiple competitors and build a Porter's 5 Forces. Or take the news headlines of the day and with your data and your competitor's data, build a PEST analysis.
As with all analysis, it's what you do with it afterwards that really matters, but using generative AI here can dramatically speed up the process to analysis, giving you something to react to and something to think about.
Part 5: Wrapping Up
The transformation, to the extent there is one here, is that we're able to take data at a much larger scale, and from the customer's point of view, to build competitive analysis. Marketers - and I am very much in this category - spend so much time fixated on what a competitor is doing, not realizing that it's far more important what our competitor's customers are doing that really matters.
If a customer of ours is unhappy with us, we might have a chance to win them back if we're clear about what our weaknesses are. If a customer of our competitor is unhappy with them, we might have a chance to win them to our side. If we're so focused on what the competitor is doing, and not what the customer is saying, we'll miss those opportunities.
Use generative AI with your data and your competitor data like this, and you'll find insights faster than ever, giving you more opportunity to take action faster, avoid being blindsided by what customers really want, and stay laser focused on the customer.
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