Companies face extra challenges if they provide solutions that don’t fit into categories. It’s especially serious for start-ups.
Category creation is hard, and requires deep focus on customer value.
One common approach is to stress your solution’s similarities to an existing category and to try to appear to fit into it. It’s a bit like the saying in English “to be a cuckoo in the nest.”
The other attempt is to create a new category (CCgroup has an excellent factsheet on the category creation process). Giant vendors like SAP and IBM can do that, and even smaller firms like eRoom, created the Digital Workspace category, have done so.
Vendors usually fail when they attempt to encourage analysts to create categories. Before its acquisition in 2014, SageCircle was the most trusted analyst relations consultancy. Amusingly, it claimed a 100% success rate on category creation projects because its clients always took its advice not to attempt them.
Over the last few years, my colleagues and I at the Analyst Observatory have spoken with analysts about how they create categories. They tell us there are many factors to assess when evaluating the creation of a new category.
Categories must seem realistic and natural.
It’s hard to draw these different criteria together, but they seem to assess two major factors.
- First, how realistic is it that this category will come to life? Does it feel like a category that has enough potential to make it commercially viable, for the buyers, sellers and analysts? A realistic market is one that is not so wide that is overlaps with other categories, and also not so narrow that only a few firms can genuinely fit into it. A realistic market must be economically viable.
- Second, how naturally does it fit into the categories around it? Something is said to be natural if it is in accordance with the nature of, or circumstances surrounding, someone or something. Does this category reflect valuable business processes and increasingly common use-cases? Is the category easy to grasp? Is what we call involution a factor? Is there a name that’s familiar to the ear because of the way it related to other categories? These assess its legitimacy.
Comparing these two factors, we get something like this.
The birds in the menagerie
Viewed this way, the cuckoo is not the only bird in the menagerie.
- Eagles. These are the most successful categories. These are markets that are commercially viable and with a definition that’s easy to share and use.
- Black Swans. These are the next most effective categories. They make sense, but the market might be too small for it to attract smaller analyst firms.
- Dodos. These markets sound viable, but they are too vague or artificial to take off. Often they describe technologies out of context rather than valuable solutions.
- Rainbow Ravens. The categories are neither commercially viable nor meaningful.
The example of credit technologies
Credit Risk is an intriguing example. Organizations assess many kinds of risk with both point solutions and enterprise-wide suites. There is an emerging Credit Tech stack that includes AI, credit risk solutions, credit bureaux, modelling technologies, data enrichment services and the use of alternative data that credit bureaux don’t have. It’s a substantial market with a growing number of providers testing out new business models for lending, going direct or through non-financial channels. Even so, no analyst firm has a formal category for credit technologies.
We think this points to the lack of engagement of those solution providers with analyst firms and their lack of understanding that a formalized market would expand both markets: the providers’ and the analysts’.
On Thursday 30 January, 2020, we’re hosting a webinar to share some of the research we’re conducting with analysts. We’ll share their reactions to our menagerie, and their thoughts about the way they assess and create new categories.
To get your free invitation for the webinar, subscribe to our ‘Analyst Equity’ newsletter at http://bit.ly/MenagerieWebinar .
