Building a Customer Feedback Loop for Ecommerce

Explore top LinkedIn content from expert professionals.

Summary

Building a customer feedback loop for eCommerce involves creating a systematic process to collect, analyze, act on, and measure feedback to improve products, services, and customer satisfaction. This approach turns customer insights into actionable changes that drive growth, engagement, and loyalty.

  • Open feedback channels: Make it easy for customers to share their feedback through multiple touchpoints, such as surveys, social media, or customer support interactions.
  • Analyze and prioritize: Consolidate feedback from all sources, identify recurring themes, and focus on implementing changes that address significant customer pain points.
  • Close the loop: Communicate with customers by acknowledging their feedback, updating them on progress, and showing how their input has shaped improvements.
Summarized by AI based on LinkedIn member posts
  • View profile for Aakash Gupta
    Aakash Gupta Aakash Gupta is an Influencer

    The AI PM Guy 🚀 | Helping you land your next job + succeed in your career

    289,557 followers

    Getting the right feedback will transform your job as a PM. More scalability, better user engagement, and growth. But most PMs don’t know how to do it right. Here’s the Feedback Engine I’ve used to ship highly engaging products at unicorns & large organizations: — Right feedback can literally transform your product and company. At Apollo, we launched a contact enrichment feature. Feedback showed users loved its accuracy, but... They needed bulk processing. We shipped it and had a 40% increase in user engagement. Here’s how to get it right: — 𝗦𝘁𝗮𝗴𝗲 𝟭: 𝗖𝗼𝗹𝗹𝗲𝗰𝘁 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 Most PMs get this wrong. They collect feedback randomly with no system or strategy. But remember: your output is only as good as your input. And if your input is messy, it will only lead you astray. Here’s how to collect feedback strategically: → Diversify your sources: customer interviews, support tickets, sales calls, social media & community forums, etc. → Be systematic: track feedback across channels consistently. → Close the loop: confirm your understanding with users to avoid misinterpretation. — 𝗦𝘁𝗮𝗴𝗲 𝟮: 𝗔𝗻𝗮𝗹𝘆𝘇𝗲 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 Analyzing feedback is like building the foundation of a skyscraper. If it’s shaky, your decisions will crumble. So don’t rush through it. Dive deep to identify patterns that will guide your actions in the right direction. Here’s how: Aggregate feedback → pull data from all sources into one place. Spot themes → look for recurring pain points, feature requests, or frustrations. Quantify impact → how often does an issue occur? Map risks → classify issues by severity and potential business impact. — 𝗦𝘁𝗮𝗴𝗲 𝟯: 𝗔𝗰𝘁 𝗼𝗻 𝗖𝗵𝗮𝗻𝗴𝗲𝘀 Now comes the exciting part: turning insights into action. Execution here can make or break everything. Do it right, and you’ll ship features users love. Mess it up, and you’ll waste time, effort, and resources. Here’s how to execute effectively: Prioritize ruthlessly → focus on high-impact, low-effort changes first. Assign ownership → make sure every action has a responsible owner. Set validation loops → build mechanisms to test and validate changes. Stay agile → be ready to pivot if feedback reveals new priorities. — 𝗦𝘁𝗮𝗴𝗲 𝟰: 𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝗜𝗺𝗽𝗮𝗰𝘁 What can’t be measured, can’t be improved. If your metrics don’t move, something went wrong. Either the feedback was flawed, or your solution didn’t land. Here’s how to measure: → Set KPIs for success, like user engagement, adoption rates, or risk reduction. → Track metrics post-launch to catch issues early. → Iterate quickly and keep on improving on feedback. — In a nutshell... It creates a cycle that drives growth and reduces risk: → Collect feedback strategically. → Analyze it deeply for actionable insights. → Act on it with precision. → Measure its impact and iterate. — P.S. How do you collect and implement feedback?

  • View profile for Oji Udezue

    AI Product Expert. Ex Chief Product Officer @ Typeform. Ex CPO @ Calendly. Ex Product Lead @ Twitter (Creators, Tweets, DMs, Spaces, Communities, B2B ads), @Atlassian, @ Microsoft. Boards.

    16,043 followers

    Closing the loop on customer feedback is an art — but a crucial one for driving product growth. Here's how to do it: 1. Open the channels Make it seamless for customers to submit feedback through your product, community, and other touchpoints. 2. Analyze and prioritize Identify the highest-impact issues across your feedback sources. Prioritize those areas accordingly. 3. Acknowledge receipt Even a simple, automated response goes a long way in making customers feel heard when they take the time to share thoughts. 4. Provide updates Keep the conversation going. Follow up with customers who submitted feedback to share how you're addressing their issue. 5. Implement and iterate Take action on the prioritized issues. Continuously improve based on renewed feedback. The bottom line: Customers who feel listened to are more invested in your success. Treat their feedback as a dialogue, not a monologue.

  • View profile for Thibaut Nyssens 🐣

    Sr. Solutions Engineer @ Atlassian | founding GTM @ Cycle (acq. by Atlassian) | Early-stage GTM Advisor

    8,996 followers

    I talked with 100+ product over the last months They all had the same set of problems Here's the solution (5 steps) Every product leader told me at least one of the following: "Our feedback is all over the place" "PMs have no single source of truth for feedback" "We'd like to back our prioritization with customer feedback" Here's a step-by-step guide to fix this 1/ Where is your most qualitative feedback coming from? What sources do you need to consolidate? - Make an exhaustive list of your feedback sources - Rank them by quality & importance - Find a way to access that data (API, Zapier, Make, scraping, csv exports, ...) 2/ Route all that feedback to a "database-like" tool, a table of records Multiple options here: Airtable, Notion, Google sheets and of course Cycle App -Tag feedback with their related properties: source, product area customer id or email, etc - Match customer properties to the feedback based on customer unique id or email 3/ Calibrate an AI model Teach the AI the following: - What do you want to extract from your raw feedback? - What type of feedback is the AI looking at and how should it process it? (an NPS survey should be treated differently than a user interview) - What features can be mapped to the relevant quotes inside the raw feedback Typically, this won't work out of the box. You need to give your model enough human-verified examples (calibrate it), so it can actually become accurate in finding the right features/discoveries to map. This part is tricky, but without this you'll never be able to process large volumes of feedback and unstructured data. 4/ Plug a BI tool like Google data studio or other on your feedback database - Start by listing your business questions and build charts answering them - Include customer attributes as filters in the dashboard so you can filter on specific customer segments. Every feedback is not equal. - Make sure these dashboards are shared/accessible to the entire product team 5/ Plug your product delivery on top of this At this point, you have a big database full of customer insights and a customer voice dashboard. But it's not actionable. - You want to convert discoveries into actual Jira epics or Linear projects & issues. - You need to have some notion of "status" sync, otherwise your feedback database won't clean itself and you won't be able to close feedback loops The diagram below gives you a clear overview of how to build your own system. Build or buy? Your choice

Explore categories