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6 Tips for Making Customer Insights Actionable

  • Customer Experience, Product design, Strategy

Support logs are one of the most important sources of customer insights. These ‘insights’ are often ignored or sidelined by other departments’ teams because they are mistrusted or lack context.

IDEAS IN BRIEF
6 Tips for Making Customer Insights Actionable
  • Support logs are one of the most important sources of customer insights, but they’re often ignored or sidelined by other departments’ teams because customer insight isn’t trusted in general.
  • To trust customer insight, you need to make sure it answers these two questions:
    • Is the information provided something I can actually make a business decision based on?
    • How much will it matter if I do make a decision based on it?

6 characteristics of actionable insights:

  1. Contextualized. There are a few ways to contextualize customer insight: volume, sentiment, tying it to outcomes data.
  2. ‍Insightful. Insightful customer feedback says something new and useful.
  3. Fast. Try looking at improving speed to insight by tagging ‘reasons for contact’ in support tickets and using NLP to sort them faster.
  4. Granular—the devil is in the details. Customer feedback surveys are often not actionable without a further root cause analysis; answers are often too high level or generic.
  5. Statistically Significant. It’s easy to get hung up on quantitative measures, and it takes a lot of time to sift through qualitative feedback, and usually, only a small sample is taken. How can large business decisions be made without statistically significant evidence?
  6. Unbiased. There are two main buckets of customer survey bias to avoid: response bias (how the actual survey questionnaire is constructed) and selection bias (the results are skewed a certain way).
Read the full article to get ideas on how your teams can start getting meaningful insights from support logs.
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A stakeholder’s perspective on engaging in research

Some practical tips on how to engage decision-makers in research.

IDEAS IN BRIEF
A stakeholder’s perspective on engaging in research
  • Decision makers should be involved in the research process as much as possible to have full context over who was spoken to and what was learnt during a study.
  • Prioritise decision makers attending as many research sessions as possible to avoid bias from only a small number of sessions.
  • Create opportunities to give and collect feedback. Allow the researchers and the stakeholders to have an open line of communication throughout the process.
  • Consider up skilling and supporting stakeholders in running research projects when needed.

Read the full article to get more details on stakeholder engagement in UX research.

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6 Tips for Making Customer Insights Actionable

Support logs are one of the most important sources of customer insights but are often ignored by other departments’ teams because they are mistrusted or lack context.

IDEAS IN BRIEF
6 Tips for Making Customer Insights Actionable
  • Support logs are one of the most important sources of customer insights, but they’re often ignored or sidelined by other departments’ teams because customer insight isn’t trusted in general.
  • To trust customer insight, you need to make sure it answers these two questions:
    • Is the information provided something I can actually make a business decision based on?
    • How much will it matter if I do make a decision based on it?
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Law of diminishing returns, design and decision making

  • Behavioral Science, Business Value and ROI, Contextual User Studies, Design Theory, Research Methods and Techniques

How do you know if there’s still room for improvement?

IDEAS IN BRIEF
Law of diminishing returns, design and decision making
How do you know if there is still room for improvement in the experiences you design?
  • The law of diminishing returns, a widely used concept in Economics that shows the relationship between investment (time, money, resources) and benefits can help Designers, UXers and Product Owners/Managers make better design, product and business decisions.
  • The Law of Diminishing returns is a bell curve:
    • Section 1 – curving upwards: is the fastest growing part of the curve, which means that efforts invested provide a more than proportional return.
    • Section 2 – leveling off: along this part of the curve we still see returns on our investment, and will keep decreasing as we approach section 3, as the curve becomes less and less steep.
    • Section 3 – curving downwards: here the slope starts to go down, meaning that our efforts stop having positive returns. This means it doesn’t make sense to keep investing (effort, resources, etc.).
  • Knowing how this curve works and where in the curve your problem lies is key so you don’t invest effort into something that doesn’t make sense to optimize. 

Read the full article to learn more about the different ways that the law of diminishing returns can be applied to design problems.

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Best Practices: Designing autosuggest experiences

  • Accessibility, Customer Experience, Interaction Design, Interface and Navigation Design

8 design recommendations for search bar & autosuggest patterns

IDEAS IN BRIEF
Best Practices: Designing autosuggest experiences
Here are some best practices recommended for the search bar & autosuggest patterns based on the analysis of user-typed queries & query formulation from about 50+ search bars.
  1. Scoping. Allow scoping if your app has multiple types of entities. Please note that scoping is not a mandatory step in the search workflow. It is only used to aid faster contextual suggestions.
  2. Autocomplete. Add Autocomplete as the top suggested item.
  3. Advanced Search. Give advanced search capabilities if your website/app has a huge volume of information and a dedicated search results page.
  4. Recent Searches. Always present recent search queries, especially in Zero State. To ensure high-quality suggestions in zero states, it’s better to have a threshold. It means a query needs to be executed several times before it ends up as a potential suggested term.
  5. Shorter suggestion lists. Limit suggestions to less than 10 list items. It is also recommended to avoid using the scroll paradigm in search suggestions.
  6. Grouping Suggestions. Always add labels and visual grouping for diverse information types.
  7. Enable conversations. Introduce conversational search experiences. Leveraging NL models to introduce voice inputs and question-answer framework can save a lot of time.
  8. Autocorrect & Clear queries. Assist with typos, erase queries, and suggestions. Additionally, provide users with an option to clear their search results in the search bar and equip them to remove their previous searches.
Read the full article below to get a breakdown of each of these best practices and learn about the research and concepts behind them. 
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