As a PM every day, we use data to make decisions about our roadmaps. Customer feedback is very important, and having closed feedback loops and processes is even more important.
Voice of the Customer/Sentiment in roadmap decisions
around new feature releases
Identify friction points to improve workflows/effort scores
Identify potential advocates
Identify potential at-risk customers
These are high-level goals for creating closed-loop feedback and how you can use all this data in roadmap decisions.
Low survey response rates with emails
Effective Action Plan
scalability to run a feedback program
1. Identify your goal and the eligibility criteria
Define your objectives of the surveys, and whose opinion matters.
2. Create an action plan
Identify potential at-risk customers to reduce churn | Incorporate product risk in roadmap decisions | Leverage Promoters to be your advocates.
3. Leverage technology to scale
Automated email follow ups to in-product responses | CTA/Slack updates for CSM to follow up | Survey Response Analysis for PMs/PMMs.
4. Standartize/Centralize your efforts
Centralize multiple feedback programs, with multiple teams and timelines, to avoid fatigue/inconsistencies.
Combining this qualitative and quantitative feedback, and then this quantitative data, keep thinking about two things - feedback and survey and product usage analytics, which we should combine with this data and see what trends appear, confirm this with a hypothesis and qualitative feedback data that you hear from your customer teams.
Segmentation, cohortization of your customers, this is very important.
Act on the feedback, look at the feedback, categorize it - it's really a request for a roadmap or an improvement.
Map it to a Timeline (Types of Feedback)
Defining your feedback goal will be very important.
The responder column helps you determine if this feedback is aimed at end users.
Then you define what the frequency is.
This is a good way to think about when you apply a closed loop feedback program.
Once you define your goal, respondents tie it to a timeline.
Slice the data by various cohorts
Analyzing and grouping your data is essential so that you can focus on the right persona, the right cohorts when making decisions, as well as giving feedback to your client team.
Tailoring is very important in the life cycle and the customer journey.
The change in the service team that we need to make, this change in the product flow that I need to make, helps you understand the area of improvement in customer experience, and where you know there can be delays. And how can we shorten that time to add value to our customers.
Gather user priorities from different cohorts before and after the release.
Once you make changes to your product, capture their post-release mood.
A very powerful tool is surveys and feedback to incorporate your customer voice into your roadmap, as well as getting ahead of any at-risk leads or customer churn.
Using Customer effort score – triggered contextually
Collecting comments
Prioritize based on
Stage
Persona
Revenue impact
Long term strategy
To do closed-loop feedback effectively, you need to be:
Timely - you need to act on the feedback shortly after it`s provided.
Accurate - you must have a clear, specific idea about the customer`s relationship with you to date and the events/usage that led to their feedback.
Proportionate - different customers will have different needs. Tailor your response.
Set response and cohort based automated email follow-ups.
Set CTAs for your CSMs to follow up for High Touch Segments
Conduct 1:1 interviews to learn about new challenges-
Provide guidance
Review with Product Team for specific roadmap changes.
Collect feedback from beta programs and early-access users before GA
Use release surveys before & after a release to learn what works and what doesn`t
Message upcoming roadmap items.
Tracking Product Risks
CSMs can provide invaluable product feedback from strategic accounts.
Enterprise account can impact retention & expansion metrics dramatically
Pms should balance feature requests and held accountable for revenue attribution.
Insights to Action
Measure of user sentiment
Visibility into Customer Journey:
CS: Early insights into renewal risk
Product: User feedback for product roadmap
These are good reference points to refer to. And also double the number of surveys with multiple questionnaires.
Listen, use your qualitative and quantitative data, look at product usage data, look at survey data, talk to your customer teams, put it all together and make your decision to figure out how to analyze that data. Analyze data based on the use of the customer segment lifecycle and determine an action plan based on this. Either provide recommendations to feed your customers or make road decisions and changes.
Harshita Banka, Gainsight Product Leader