What's the difference between a persona and a customer segment?
Personas are a new way of distinguishing between different types of customers that is based on how and why customers think and choose - their motivations - rather than on demographic, ethnographic or behavioral attributes. For any particular project domain, there will be between five and nine different personas that represent the different rational and emotional aspects of someone who may or may not adopt something new. One interesting thing about personas is that there is not a one-to-one mapping between a persona and a person. A person is a complex mix of different personas in different situations.
Why are qualitative results better than quantitative results in the front-end?
There is an expression - never let your precision exceed your accuracy. Don't use a 100 point scale when a 3 point one will do. the front-end is characterized by uncertainty, ambiguity and incomplete information. You are trying to gather, synthesize and make sense out of new information in order to make decisions about which path to take or which alternative to choose. There is no oine truly 'right' answer. There are better and worse answers. This environment begs for knowledge creation and decision making tools and methods that rely on the qualitative distinctions that matter. The quantitative analysis comes later.
For more thought on this topic see 'Before Market research'.
Why distinguish between opportunities and solutions?
An opportunity is an unmet want, a solution is a means to satisfy that want. Wants consist of both needs and desires, the avoidance of pain and the seeking of pleasure, that motivate all of us. If you focus on solutions too soon, without understanding the complex web of personas and wants, you will miss the best solutions. It is not easy to separate opportunities from solutions. Whenever we identify a problem, an issue, a point of pain, we want to address it. We naturally feel uncomfortable when we identify an opportunity and don't have a solution in mind. But if we can overcome this discomfort. If we realize that it is not just up to us to 'solve the problem'. If we can delay the gratification that comes from coming up with the elegant solution. If we can explore all of the subtleties and nuances of the opportunity before we solve it, the solution that we do eventually come up with will be that much more compelling and valuable.
Why explore for new opportunities?
The exploration of, and discovery of, opportunities is an interesting activity that is often hidden and overlooked in an organization. Many opportunities seem to just 'emerge' from the normal course of doing business, or from an executive's insight or opinion, or from an idea management system, or from water cooler conversations or personal passions. This opportunistic approach to uncovering new opportunities is valuable and should be encouraged. There is, however, another, more structured, more comprehensive and more productive way. One that is based on sound research into how to explore vast, new areas and discover the most significant and relevant things of potential value. This methodology uncovers more and better opportunities in a shorter time than alternatives. And it focuses proper attention on the opportunity, rather than the solution.
Learn more about opportunity discovery.
Why do we create software models of personas?
Personas are the representation of how different types of customers think and choose. Persona descriptions always have a narrative, something that can be read that lets the reader put themselves in the shoes of the persona and empathize with the persona. this is an extremely valuable thing to have and usually, this is where personas stop. Turning this narrative into an actual software model of the persona, however, gives you even more.
- Makes all of the ‘soft’ information - needs, desires, experiences etc. - explicit and structured.
- Direct traceability to sources. Can identify the specific people, and what they said, that resulted in the model component
- Explainability and consistency. Can examine the model and explain why an adoption curve is what it is. The results are comparable.
- Reusability and independence. You don’t have to have thought of all the possible alternatives a-priori. If you think of something new, you can run the model again
- It’s a model! You can play with it, do sensitivity analysis and what-if’s and if you don’t like the assumptions, you can change it!
Find out more about persona models.
How do we validate results?
Innovation metrics are difficult. The ultimate metric is commercial success but that can take years after the initial 'innovative concept' was conceived and chosen. A metric that lags the innovation process by potentially years is ok for long-term assessment, but isn't useful to track and judge the daily, weekly, and monthly innovation activities and projects that need to be the on-going life-blood of an effective front-end process. Here are some metrics we use to validate the results we achieve on an on-going basis.
- Size and diversity of the communities we create. Number and quality of engagements. This gives an indication of how outwardly focused you are and how much you are seeking new knowledge.
- Number of opportunities discovered, the number and kind of opportunities that make it through the discovery pipeline and the 'crowd' assessment of the opportunities
- Number of solution concepts created, the number and quality of the solution concepts that are modeled for adoption, the adoption scores of the concepts
- Comparison of front-end outputs (new solution concepts) with other new product development projects. using downstream market research metrics to compare results.
- Economic assessments of business potential.
- Marketplace success.