As telecom and technology markets are continually disrupted, our approach to their specific market research challenges needs to evolve with them.
What are you to do when you’re facing intense price competition, losing volume to the competition or launching new product innovations? Today’s digital consumers have more telecom and technology product options than ever before. For marketers in these industries, historical data will only take you so far when optimizing your product portfolio.
And the challenge only becomes more complex when you consider how today’s empowered consumers make purchase decisions differently than they did just a short time ago.
To successfully optimize your pricing and portfolio, with a seemingly unlimited amount of choices amidst this rapidly changing market, you need a more a reliable market research approach for identifying which products consumers prefer.
Choosing between conjoint research models
You may not be a conjoint research expert (we just happen to be), but we can tell you that conjoint analysis is currently the go-to methodology when it comes to these types of complex pricing and portfolio optimization research projects. There are two well-known models for conjoint analysis:
- Choice-based conjoint (CBC), where we offer respondents a set list of products, regardless of what kind of user they are or how they respond, in order to reveal their preferences.
For example, would you prefer 2GB of data for X amount or unlimited data for X amount?
- Adaptive Choice-based conjoint (ACBC), where you ask the respondent to build their own best-prefered product.
For example, asking respondents the amount of minutes they want, the amount of data, and so on, quite literally informing which products they prefer and we use this information to create more relevant questions that follow.
(Check out these examples for a clear idea of how conjoint analysis works.)
Having personally worked on hundreds of conjoint studies over the years, I often advise clients on which pricing challenge requires which method. For example, for a fast-moving consumer goods brand looking to set a price for a new paper towel product, I’d recommend the CBC model because you’re limited to looking at product and price, vs. other factors.
However, when you have more products choices today, with multiple characteristics, such as telecoms or those of many technology products, there is a need for a more adaptive solution. Having used ACBC for multiple projects, and seeing this might be too aggressive in its level of adaptiveness, we saw the need to develop a new method; one that sits between the two current choice models and provides the best of both worlds.
Enter adaptiveness in choice modeling
It's really difficult to ask people to make a choice between 100 products, because cognitively they can’t. You might simplify this by asking them to make a choice between four products and try to predict what they would do in a market with more than 100, but that's not a real-life situation. This realization led us to develop a new methodology more suited to the specific and evolving needs of telecoms and technology brands today.
We call this preference-based conjoint (PBC) and it’s a more personalized research approach.
How does it work? Everyone starts at the same point within the questionnaire, but depending on how the respondent answers, the product options will become more and more specific to them. This adaptive process allows us as market researchers to narrow down precisely which characteristics the consumer prefers.
This new personalized method is so effective because we get to their preference quicker and more accurately. The resulting insights are based on what they're telling you - in a product choice, not in a stated question, because you can't trust people with stated questions.
Choosing the conjoint experts
It’s no coincidence that when the large consulting firms start a sophisticated conjoint project, they turn to SKIM. Since 1979 we've helped the world's top brands to understand the choices their customers make by employing choice modeling and analysis. In fact, my methodology colleagues and I just returned from a conference where we trained market research professionals as a preferred partner of Sawtooth Software, the global leader in conjoint analysis software solutions.
Some SKIM research methodologists have been involved in over a thousand conjoint studies, giving them unparalleled hands-on experience in the field. It’s this combination of experience and technology that enables our analysts to take strides in the area of conjoint—for example, innovating a .
No matter how complex your business question is, our experts gladly use their creativity and unbeatable analytical chops to come up with novel—yet solid—research approaches to solve it.
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