Choice overload is a problem not only for users but also for investment decisions in product features that product managers, engineers, and designers have to make.
Providing too many product features requires greater mental effort from users, also called choice overload. When users get overwhelmed by too many choices, they tend to either:
- Use heuristics, fixing on a couple of features that matter to them and ignoring the rest, which may lead to buyer’s regret; or
- Engage in an exhaustive analysis of the pros and cons that lead to analysis paralysis, and often no choice at all as they can decide.
In either case, the product development team needs to identify the relevant features that should be developed and presented to different user segments. This applies to both physical and digital products.
Fortunately, there are research methods for that.
What Causes Choice Overload?
First, we need to identify if the choice overload stems from:
- Too many options when selecting and/or using the product/service (e.g. many ways to do the same operation, many entry points, irrelevant features that clutter user interface but hardly used, confusing information architecture, etc.).
- Lack of clarity on key benefits and product features due to too much information about the product/service (e.g. long lists of product features and benefits, many different product tiers and versions, etc.).
Although these issues may be connected, one is about actual product use and the other is about product communication. Product communication and use should be in sync to avoid:
- Delivering a bad user experience during product use despite great product concept descriptions.
- Rejecting products that can deliver a great experience but were poorly described as concepts.
Research For Eliminating Choice Overload
When you have a long list of potential product features that can lead to choice overload producing either buyer’s regret or no choice due to analysis paralysis, there are several types of research you can conduct to facilitate user choice and guide the product development process.
1. In-depth interviews
A deeper probing of needs and motivations for using a product/ concept idea can provide a clear idea of the most important perceived benefits and potential product /brand positioning. This type of interviews can be combined with other testing methods.
2. Contextual Inquiry
Once you identify the top tasks, it is time to observe how users conduct them and ask probing questions as needed to get a deeper understanding of behaviors involving product use in the users’ natural environment.
3. Moderated User Testing
Moderated user testing a task-based interview approach we use to understand the user experience to detect problems in user interaction with digital products (websites, software, apps). Ideally, the selection of tasks is based on top task analysis.
4. Top Task Analysis
This approach aims at identifying the most common and critical tasks users do when using a product/service to help identify product features we need to develop. We can base this type of analysis on data analytics already collected (e.g. Google Analytics) or surveys designed for this purpose.
5. Unmoderated, Remote User Testing
This type of testing allows us to reach a larger sample of users with relevant tasks and quantify several metrics related to the user experience for digital products. It can help us quantify navigation paths, errors, feature utilization, time on tasks, etc.
6. MaxDiff Analysis
MaxDiff is a trade-off technique used to prioritize product features and benefits for any type of product or service. It is based on comparative choice questions which have better discriminatory power than other question types (e.g., rating scales, ranking, etc.)
7. Conjoint Analysis
Conjoint Analysis is a more advanced trade-off analysis technique that can be used to find the optimal combination of product features and benefits in the context of the competition. We also use it to optimize product portfolios for different market segments and research pricing.
8. Product Concept Testing
Concept Testing can help validate the appeal of a set of distinct product concepts when you have already a clear set of product features and benefits that differentiate them. Product concept testing can be monadic, sequential, and comparative depending on the number of concepts, timing, and budget, among other factors.
9. Positioning Concept Testing
The focus of positioning concept testing is on the selection and validation of the key benefit and supporting product features offered by the product/service. We use this type of research to make decisions related to brand positioning and product communication.
The goal is to prioritize benefits and determine which should be front and center when communicating your product and service. Do not confuse product features and benefits. Positioning concept testing can be monadic, sequential, and comparative depending on the number of concepts, timing, budget, among other factors.
10. Advertising Concept Testing
Once you decide on how to position your product/service and what product features would support that positioning, it is time to decide how you are going to communicate your product benefit(s) and supporting product features.
There are many ways to tell the same story and testing advertising concepts can help identify the most effective one. Advertising concepts can include ads for mass media (e.g. TV, radio, print, direct mail), and digital media (e.g. digital banners, email campaigns, video).
We can use this approach to test ways to highlight and compare offerings to avoid choice overload. Advertising concept testing can also be monadic or sequential and presented in the context of other advertising.
Qualitative Or Quantitative
Depending on the sample size and feedback method (e.g. surveys, in-depth interviews) the approaches below can be qualitative or quantitative.
11. In-home /Lab Product Testing
This approach puts the product or service, or at least a working prototype, in the hands of the users and requires an organized way of asking feedback through various question types. It will allow you to understand product features that matter, and any pain points users are experiencing.
12. Card Sorting
We use this technique not only to test information architecture in digital products (websites, software, apps) but also to categorize and prioritize product features and benefits for any type of product or service.
When conducted in person and with small samples, card sorting is more qualitative in nature. Larger samples allow for a more robust quantitative analysis.
Choice overload can lead to hasty purchase decision customers may regret (and lead to returns, negative word-of-mouth, one-time purchases) or decision paralysis with the associated no-purchase behavior.
There are many research techniques you can use to prioritize products, product features, benefits and messaging and eliminate choice overload.
- Quantitative research can follow qualitative research for validation purposes.
- Qualitative research can follow quantitative research to look for deeper insights behind the numbers.