Product sense: Customer feedback sources every product team should draw insights from?
Updated: Oct 8
Before we delve too deep into what is product sense, and how to go about it as a product team, let's start by thinking about our own behavior as a customer.
Recall the last time, when you shared an idea or complaint for a product. If your feedback went unaddressed for a long time, how likely are you to continue using the product?
You might be lenient for once, twice.. but if the product team keeps ignoring your perspectives for long, you will most probably walk away from the product with a bad taste.
In fact, you might even consider sharing negative reviews with others in your network.
What I am describing here, is still what we observe with a very forgiving customer.
Research suggests that 32% i.e. 1/3 of customers say they will walk away from a brand they love after just one bad experience.
Given this, it is crucial for product teams to always stay on top of their user needs, continuously engage with customers and scope urgent asks as soon as possible on the product backlog.
This is where product sense comes in.
What is product sense?
Product sense, is nothing but the ability to collate customer data, synethesize it to gain a deep understanding of what users want and developing an intuition of what would make a product great.
The challenge of product sense.
Typically, developing product sense is NOT a one-time kickstart activity. It's a continuous one throughout the product lifecycle.
It's natural for product teams to plan a lengthy customer research cycle at the start of building a product. However, the trap that many teams fall into, is not engaging with the customers on a continuous basis.
Sure, the initial customer research would help the product teams develop a sense of what the customer wants for minimum valuable product (MVP).
However, customer needs evolve regularly. Their feedback keeps changing as they interact with the product. What was relevant for users at the start might have completely changed now.
If we were to ask you to keep a tab of customer feedback across multiple channels (even if it's just 2 or 3), how good a job you think you would do on a regular basis?
Users tend to use any channel available, to talk about the products they use. They are everywhere.
Product teams can't really control where users voice their opinions.
Organizations spin up an official customer support channel. They might also provide a portal, where customers are meant to share any product ideas or requests.
However, they can't stop customers from talking on other channels.
Customers share feedback on social media.
They are talking to your sellers and customer success representatives regularly.
They are escalating tickets via emails.
They are interacting with your web chat feature.
And using any other channel they can find to make their voices heard.
So, building a rhythm of product sense depending on manual analysis of customer feedback across channels is nearly impossible. This absolutely needs automation.
Even if the team is highly disciplined, they can only reach a handful of customer feedback on a weekly or monthly basis at best.
That's where an AI copilot like Flash comes in.
Flash consolidates customer voice across multiple channels, sorts it into relevant themes and makes it available in a unified view.
Product sense: Which data should you tap into?
In order to keep a continuous tab on all user feedback across channels, product teams need to think of all potential avenues where their customers might be talking about the product, and figure out how they can operationalize insights on top of this gold mine.
Here are key customer feedback channels to consider:
Customer support interactions:
On launching products, organization typically convey a support channel for users to raise support tickets for any issues they face while using the product.
For the customers, these could be in the form of support portals or via support chats on the website.
The organizations internally use connected tools like Zendesk, ServiceNow, FreshDesk or Intercom where the data from these customer support interactions get collated.
Product teams need to tap into these customer support tickets/ interactions regularly, to get a sense of complaints or concerns that users have.
Customer collaboration platforms:
It's advisable for product companies to open collaboration avenues with users (provided of course they have teams to support an active engagement).
Collaboration platforms like Slack, Teams, WhatsApp or even GitHub (for open source) open up doors for users to directly reach out to product team members, get their answers quickly and trust taking up business dependency on the product.
Although community managers are typically on-point to respond to any user posts on these, product teams need to regularly review the feedback/ questions raised by customers so that they can develop a good sense on the current customer asks and sentiment, and also prioritize work items into their backlog.
Social media/ Discussion groups:
Users engage with other product users in open forums.
Sources like Reddit, LinkedIn groups, Facebook groups, Product Hunt etc. are actively used to voice their perspectives and get help from community members.
Now, when employed as supported company channels (for eg. a product specific sub-reddit or a managed LinkedIn group), discussions on these feedback channels are product-specific and serve as a rich source of insights for the product teams.
Beyond supported company channels (for eg. a domain or industry specific discussion group), these data sources are also an extremely rich source of insights for broader market and competitor research.
When actively listened, product teams can glean insights like customer sentiment, comparisons with competitor products, questions, appreciations and any ideas from users, voiced on these public forums.
Review sites:
Users tend to submit ratings and reviews on products on websites like G2, Capterra or even cloud marketplaces (AWS, Azure and GCP).
User reviews are a direct source of whether customers are appreciating the product, and are they voicing any pros and cons of the product.
Emails:
Sales, customer success, support or even at times product managers tend to receive customer reach outs directly via email.
Now, while a product managers mailbox might be crowded more by emails from internal stakeholders which makes it difficult to continuously mine it for user perspectives, a customer-facing role like sales, customer success and support tends to have their mailboxes mainly populated by customer emails (both users and buyers).
That's another great source of customer feedback, provided all team mates are open to let their email conversations researched for customer insights.
Now, we have to be careful with this one - not to invade the privacy of team members.
Another approach could be to request customer-facing team members to diligently notate their discussions notes in systems (like Salesforce or Hubspot CRM for sellers, Zendesk for support).
However, this always runs a risk of missing out on few crucial conversations due to the manual nature of this activity - still, something is better than nothing if privacy of users' mailbox is a bigger concern.
CRM activity history:
If sellers diligently note all these customer interactions in CRM, it could be an important source to know whether customers asked for any product features, or sellers made any timeline commitments.
Major CRMs include Salesforce & Hubspot, but there could be industry-specific or niche CRM systems that your organization might be using.
Sales/ Customer success meetings:
Users tend to voice their product asks or complaints in front of any organization team member they can get hold off.
So, while the seller or customer success team member might have scheduled a meeting with customers for a different agenda, users use the opportunity to bring forth any of their product perspectives.
Now, there are few ways to ensure insights from these meetings are known to product teams -
Either ask your sales or customer success team members to note customer feedback and convey via emails,
OR
Product teams members could rotate and attend customer meetings organized by sellers or customer success folks from time to time hoping to be present in the right meetings
OR
Implement a solution which automically extracts the right insights from meetings and surfaces in front of product teams.
Flash aligns with the last approach by integrating sources like Google Drive, Zoom, Fireflies and more, thereby ensuring no customer feedback voiced in meetings gets missed.
Discovery interviews:
Product managers or UX researchers proactively organize discovery interviews to validate any hypothesis/ assumptions with users.
While this approach can reach only a handful of users, this is a very rich source of insights as product is the clear agenda in these meetings.
Typically, organizations tend to use Google Meet, Microsoft Teams or Zoom to conduct these meetings - so their their transcripts are available and can be analyzed to draw intelligence.
Surveys:
Now, while interviews/ meetings have a limited audience reach, one of the techniques product teams use to cast a wider research net is surveys.
There are multiple avenues - in-app quick surveys, Net Promoter Score (NPS) surveys or multiple question study surveys.
Our recommendation is to use short quick surveys to validate assumptions with just 1 or 2 questions to keep respondents unbiased.
In fact, LinkedIn serves as a great platform to collect such survey feedback quickly from a wide audience. All the better, if you have Sales Navigator access to ship the survey as email to a finely targeted audience.
Our opinion is that larger multi-question surveys are ok occassionally, however they irk the respondents, tend to include biased questions and discourage the audience from responding.
Focus group discussions:
If you think about it, FGDs (focus group discussions) are simply another form of customer meetings.
Just that it's likely to be conducted with a group of users across multiple customers.
Still, mining these FGD recordings is very similar to insights from direct customer interviews.
You can extract ideas, complaints, appreciations, questions or any compete mentions.
It might get tricky though to extract which user from which organization within the FGD gave what feedback - that requires some advanced AI or manual annotation.
In-app feedback:
Many product teams deploy in-app widgets which they can use to get inputs, right when users are using the product.
It can be a flexible way to get any type of quick feedback - how they find the feature experience, their in-general NPS or sentiment, their ideas or new capability requests and so on.
Or another creative way of using in-app widgets is to simply ask time for a discovery meeting, which could later be scheduled.
This form of customer engagement is gaining a lot of adoption.
Research reports:
One other source of customer engagement, often ignored by product teams, is reports published by industry or research agencies.
Let alone the well-known Gartner or Forrester reports, there are instances where an industry specific agency feature a product in a report, and users start actively talking or evaluating the product from there.
Product teams need to keep an eye out for such opportunities, and ensure they capture the right insights and capitalize product growth opportunities from such exposure.
Other sources:
This post is more focused only on customer feedback sources to tap into, for developing continuous product sense.
One other super important source to understand customers deeply is product usage telemetry data, but that's a topic for different post.
And there are many more customer data sources like past purchases, credit history etc. but you can think of those more in the context of customer 360 rather than product sense.
A holistic product sense factors all possible avenues which offer deep understanding of the customer, so that the product team scopes the right features to accelerate product love.
Conclusion
Now, just collating customer voice from various sources is NOT enough.
In fact, let's say you put in effort and manage to implement an automation to consolidate customer feedback, it can get overwhelming pretty soon.
Think about 100s of customer quotes showing up in a dashboard on a daily basis - will you be comfortable reviewing all of them?
That's where a solution like Flash comes in.
Flash connects with customer voice sources, consolidates it and synthesizes it to surface relevant product insights in the form of ideas, complaints, appreciations, questions, compete mentions etc. in a unified view.
Moreover, we try to keep the experience dead simple, to keep the insights quickly consumable.
Now, of course, there is a whole lot more to product discovery than just consolidating customer feedback and extracting product insights from it.
Those are features that we at velora.ai are working towards, and would love to hear your perspectives - so feel free to reach out to us so we can BUILD FOR YOU.
So, what are you waiting for?
Connect with us TODAY, to explore how we can help your product teams build better.