A white space analysis maps the parts of your market where you are structurally not competing: segments, dimensions or deal types on which competitors score and you do not. It is not a brainstorm about opportunities, but a comparison of your position against that of a peer group on the points that actually decide deals.
The difference with an ordinary competitive analysis lies in the angle. A competitive analysis describes what competitors do. A white space analysis starts with the dimensions on which deals are won and lost in your market, and then places your score and that of your peer group alongside them. What remains is not a list of observations, but a matrix of gaps: dimensions where you sit below the average of your peer group, with evidence as to why.
At a company of roughly 150 employees there is often already information about competitors available: sales notes, what the commercial team hears at trade fairs, an occasional LinkedIn search. That is rarely enough to build a white space analysis on, because isolated signals do not reveal on which dimension the gap is structural and on which it is coincidence. Anyone asking how do I get information about competitors who don't publish figures runs into the same problem: it is not about more data sources, but about a fixed set of dimensions on which every competitor is scored in the same way. Without that structure, every gap remains a suspicion.
The dimensions that make a white space analysis meaningful are not universal. For a software company, implementation speed can be a deal-deciding dimension, while for a service provider it might be references in a specific sector. Which dimensions apply depends on what actually tips the scale on a go/no-go in your market, and that is something different from what is internally perceived as a strength. A management team that believes it stands strong on service may find upon testing that customers mainly compare on delivery time. That is why a white space analysis starts with establishing the right dimensions rather than filling in an existing checklist.
A gap is only a gap in comparison to something. Without a sharply defined peer group, the analysis does not yield white spots but a list of assumptions. At a mid-sized company with a few direct competitors and a number of indirect players, the temptation is great to draw the peer group too broadly, causing the scores to blur. How to properly define that group is explained in what is a peer group and how do you assemble one; for a white space analysis this is not a side issue but the foundation on which every gap rests.
A common assumption is that a white space manifests itself in price: if a deal is lost, it must be down to the rate. In practice, part of these gaps turns out to lie in dimensions such as delivery time, warranties, sector-specific experience, or the way an offer is presented. A company that lowers its prices based on a gut feeling while the actual gap lies in references closes nothing and still loses margin. Anyone who notices that deal losses are repeatedly blamed on price will find in why do we keep losing on price more and more often an explanation of how price pressure is often a symptom of a gap elsewhere in the matrix.
A white space only has value if every score is backed by a source: a tender, a job posting, a customer review, a price list. Without that source, a score is an opinion, and an opinion shifts as soon as someone else is at the table. A management team of 200 employees that identifies a gap in "implementation speed" holds something different in hand when that score is substantiated with lead times from three public tenders than when that score rests on an impression. That same substantiation also makes it possible to establish how do I know what we truly win on, because winning and losing are two sides of the same matrix.
If there is doubt about whether the gap you are running into lies in price or elsewhere, the free loss-on-price check offers a first indication: eight questions that indicate which dimension is leaking, without requiring a complete study. Establishing a gap is not the same as closing it: the latter is execution work in processes, people and systems, with a price tag that varies per situation. What that costs, and which part of it can be covered with AI, is explained in the work scan on ftetoai.com.