Of Product Comparisons and Gap Analysis
Product Management teams, are constantly looking for how to make their products better. They are always hungry for information that will make it more competitive, and more appealing than a competitive offer.
In Competitive Strategy we get frequently asked for a “Competitive Gap Analysis” to help product management answer that question. But what is it that they really want? Are they looking for justifications of a hypothesis or legitimate input on the product positioning? What product management needs is a full blown competitive gap analysis, not a side by side product comparison. The difference may be considered subtle by some, but it certainly makes a big difference.
A product comparison attempts to compare, side by side, your product offer with that of a competitor. Picture a simple table where one column lists all the features to assess; and then two or more columns with specific products with a bunch of “yes” and “no” or green checkboxes and red crosses. This is to try to understand where you can make your own product better. Many times is also used as a sales mechanism.
Below’s an example of a public facing sales tool that Toyota has on its website to aid potential customers. They compare multiple features and characteristics of the 2018 Toyota Corolla with the Honda Civic, Ford Focus, and Chevy Cruze (that doesn’t exist anymore).
What to consider for a proper Competitive Gap Analysis
It is very important to understand, that a product gap is defined by the perceived customer care about, and not by the competitor offer.
What this means is that when comparing items side by side, the categories and dimensions must come from the customer needs, not from the product itself. For example, back to our Toyota Corolla example: if we are interested in comparing the “performance category”, we need to know how much importance do customers give to the number of cylinders of the engine, the MPGs, the horse power of the engine, and the number of speeds in the gearbox. Which one of those is more important to customers today? probably MPGs, possibly nobody cares if the engine has 4 or 3 or 5 cylinders these days, what about the number of speeds in the gearbox?. If Toyota's research shows that MPGs is very important, but people don't care about the number of speeds in the gearbox, then it doesn't matter if a Corolla has 5 speeds and a Focus has 6 speeds. It is NOT a competitive gap having less speeds. Customers simply don't care, so therefore it is not a gap. All effort must be put into improving the miles per gallon of the vehicle, which customers give it a very high importance.
A common mistake is to forgo the customer research, and ask the competitive intelligence team to build a product comparison table based on product features. A good analyst needs to reach out to the customer, and not just look at the competitor product. Otherwise, it may seem as in Toyota needs to invest in a 6 speed gear box because Ford has a better product with 6 speeds. That'd be a mistake.
Weighted Gap Analysis
A data driven and analytical approach to competitive gap analysis that I like is a weighted comparison. The idea is as follows:
- List the customer care-abouts to compare. Examples could be, performance, ease of purchasing the product, technical innovations, etc. Those must come from why customers buy the product.
- Find out from customers, how much importance do they give to those care-abouts. Give them a weight from 1 (least important) to 5 (most important).
- Identify a collection of attributes that can be associated to those care-abouts, and that you can answer yes or no. Think of it as examples of those care-abouts. For example, under the ease of purchase care about you could list “can you buy the product from the internet?”, “does the customer get it instantaneously when they buy?”, etc. Answers need to be binary, a yes or a no, because you will later tally them up, and normalize results.
- Then calculate result: multiply the care about weight by the sum of positive answers you get for all the attributes of that care about and stack them in a bar graph.
I built this quick example for the Toyota Corolla comparison. Answers may or may not be correct in my example, but the framework is illustrated.
I have listed three care-abouts (Performance, Ease of Purchase, and Technology) with about 4 or 5 attributes each. Notice that we already determined the number of cylinders in the motor is irrelevant, therefore we are not adding those up. Also, notice that customers believe technology packages in these cars is far more important than the performance of the car, and they are willing to experience average pain when buying the cars. That can be seen evident in the taller gray bars of the resulting graph. So even though according to this example, the Toyota Corolla scores 0 in performance (because it doesn't have the best MPGs nor powerful engines), it scores very well where it matters: in Technology. So as a whole, the Toyota Corolla is the best one comparatively speaking.
Now, Toyota product managers, can decide whether to keep investing in Technology, or perhaps make it easier to purchase a Toyota Corolla. Honda product managers, on the other hand, could simply focus in technology and leap frog Toyota easily.
Some final tips
- Focus on providing value; not confirming a hypothesis,
- Start with the customer: ask yourself what really matters to the customer. Buying Persona profiles can help. Research (by speaking with customers) is a requirement.
- Make it analytical that can be back up by numbers.
- Don't boil the ocean. It's better to keep it simple and only to a few care about dimensions, than building hundreds of attributes in a giant data base.
Originally published on December 20, 2017.