Sachin Rekhi. Designing your product's continuous feedback loop

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This document discusses designing a continuous feedback loop for products by establishing a feedback river and feedback system of record. It defines a feedback river as an open channel for any team member to provide real-time feedback from various sources. A feedback system of record acts as a single source of truth to consolidate and aggregate feedback. Notejoy and Sales Navigator are used as examples of companies that have implemented these concepts through feedback channels, weekly meetings, and prioritizing feedback. It cautions that not all feedback should be directly implemented and that the target customer and business priorities must be considered.

Designing Your Product’s
Continuous Feedback Loop
Sachin Rekhi
@sachinrekhi
sachinrekhi.com
Founder & CEO, Notejoy

Meet Notejoy, collaborative notes for teams

Meet Sales Navigator, enabling social sales

Jeff Bezos, Amazon
“One thing I love about
customers is that they are
divinely discontent. Their
expectations are never static -
they go up. It’s human nature.
We didn’t ascend from our
hunter-gatherer days by being
satisfied. People have a
voracious appetite for a better
way… You cannot rest on your
laurels in this world. Customers
won’t have it.”

100
We built it, but they
didn’t come
200
We got out of the
building and talked
to our customers
300
We analyze metric
dashboards weekly
& commission
well-designed
research studies
Mastering customer obsession
400
We have a
continuous
feedback process
with a feedback
river, feedback
system of record,
and deep synthesis

Why 300-level customer obsession is not enough
Metrics can help
identify what’s
wrong, but not why
Research studies
are infrequent &
quickly out-of-date

Mastering customer obsession
400
● Feedback river
● Feedback system of record
● Deep synthesis

What is a feedback river?
an open channel for any team member to get
continuous real-time feedback on the product
across a multitude of sources

What are the benefits of a feedback river?
Voice of
customer directly
from the source
Real-time
feedback after
product updates
Ability to recognize
patterns across
sources

Notejoy’s feedback river
NPS
Canceled account reason
Feedback submission

Notejoy’s feedback river
Feature request vote
Feature request comment
Help search query

Sales Navigator’s feedback river
lighthouse-feedback@linkedin.com
Monthly NPS survey results
Customer survey results
Weekly top customer support issues
Weekly metric dashboards
Employee feedback
Sales team customer stories
Social media summaries
Churn survey results
Sales team questionsUX interview notes

What is a feedback system of record?
a single source of truth for consolidated and
aggregated feedback across a multitude of
sources

What are the benefits of a feedback system of record?
Speed up
processing of
feedback
Simplify
incorporation into
roadmap
Avoid recent
feedback bias

Sales Navigator’s feedback system of record
Lighthouse Feedback
● Held weekly feedback meeting with representatives from product, design,
engineering, marketing, sales, customer success
● Reviewed newest feedback items as well as updated ranking for features /
problem areas
● Moved important items into bug fix sprints or consideration for upcoming
roadmap

So now I just implement features from
the feedback system of record in
priority order, right?

“If I'd asked people what
they wanted, they'd have
asked for faster horses.”
— Henry Ford
Well, at least we know they
find traveling by horse to
be too slow!

Is the feedback from your target customer?

User vs business priorities
Acquire
Activate
Engage
Retain
Upsell
Refer

Top feature requests that were never implemented
LinkedIn Sales Navigator
Export LinkedIn profiles to Salesforce
Provide LinkedIn member email addresses

Want to learn more?
125+ product essays, videos, podcasts at
sachinrekhi.com

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Godard Abel is CEO of G2.com, Inc, a business software review website, which he co-founded in 2012. Previously Godard served as CEO of SteelBrick which was acquired by Salesforce in 2016 where he subsequently served as SVP/GM of the SteelBrick business unit until May 2017 when he left to refocus on entrepreneurial adventures. Godard previously co-founded and as CEO built BigMachines into a leading software-as-a-service provider which was acquired by Oracle in 2013. Before entering the technology industry, Godard consulted for McKinsey & Company and advised leading manufacturers in the U.S. and Germany on strategy development and business process improvement. Godard was named to the Tech 50 list by Crain’s Business Chicago in September 2014 and to the Chicago Entrepreneur Hall of Fame in 2011. He earned an MBA from Stanford University and both a B.S. and M.S. in engineering from the Massachusetts Institute of Technology. He is a member of the 2016 Class of Henry Crown Fellows and the Aspen Global Leadership Network at the Aspen Institute. Speech Overview: Based on unique insights gained from g2.com software marketplace, exploring trends in the global software industry and how software innovators can overcome the crisis of customer trust.

Zeb Evans, ClickUp. From $0 to $20M ARR in 2 Years: Bootstrapping to Natural ...

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The document discusses the differences between natural product-market fit (NPMF) and artificial product-market fit (APMF). It notes that NPMF is achieved through bootstrapping, winning organic users, listening to feedback, and iterating quickly. In contrast, APMF is achieved through buying growth, which can lead to addiction and lack of long term viability. The document advises that after achieving NPMF through bootstrapping, companies should continue listening to feedback to further improve their product.

Namir Anani, ICTC. Economic Resiliency in The Face of Adversity

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The document discusses economic resiliency in the face of adversity. It notes that the Information & Communications Technology Council (ICTC) acts as a strategic coach for the digital-based economy. It also discusses five global forces causing non-ordinary disruption, including technology, environmental trends, urbanization, the gig economy, and trade/economy. Additionally, it provides data showing that the ICT industry has increased employment by 9% since February despite COVID-19, and outlines growth in several ICT-related industries and investments.

Mada Seghete, Branch. Mobile Growth Trends

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The document discusses how mobile usage and app usage increased significantly during the COVID-19 pandemic. It summarizes trends in mobile activity across different app categories during the pandemic, including increased usage of social apps, grocery apps, finance apps, and decreased usage of travel, events and music streaming apps. It also discusses challenges for brands in 2021 related to platform fragmentation, changes to ID tracking on iOS 14 limiting cross-app tracking, and the need to focus on retention instead of acquisition as mobile usage grows.

Julia Petryk, MacPaw. Product PR: a how-to guide

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Julia Petryk is the Head of PR at MacPaw, a globally acclaimed developer from Ukraine. Julia has 10+ years’ experience in digital marketing and online communications. She currently oversees the MacPaw’s global PR strategy, leads a team of PR practitioners, and maintains the company’s online presence in Western media. Julia is a mentor for tech startups and an author of her own online course “Product PR”.

Yaroslav Ravlinko, Intellias. You don’t need Kubernetes. You need to understa...

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Yaroslav has been working in IT industry since 2008, delivering more than 50 projects in different domains across the globe. In the last few years, he’s been cooperating with high profile clients to provide guidance and support on their organizations’ journey to digital transformation. He worked with the biggest retailers in North America and tech giants such as Cisco, Dell, Suse, and Canonical. His most significant recent project is Data Science Platform (ML) developed in collaboration with Dell, Canonical, SUSE, and Intel (officially announced on February 2020). Today, he is a head of the IT Advisory Group at the Intellias Technology Office. Speech Overview: We will discuss the reasons why Kubernetes won’t change a lot outside the infrastructure providers’ world and why it’s not the best option for you. Why is it more important to understand the concept behind this platform rather than use Kubernetes itself? How Kubernetes managed to become the platform for computation, while OpenStack didn’t? What other alternatives might work better for you? When to use and not to use Kubernetes?

Yaroslav Novytskyy, Anton Vasylenko, N-iX. Migrating to the cloud: options an...

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Yaroslav is in software development focusing on Cloud since before the Cloud. It is his work and hobby at the same time. Concepts, architecture, solutioning and hands-on implementation along with leadership, management, and processes were his responsibilities working and consulting in Canada, USA, Ukraine, Austria. Anton worked as Engineering Manager, leading 5 products at the same time. Took part in due-diligence, importing companies

Kostiantyn Bokhan, N-iX. CD4ML based on Azure and Kubeflow

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Kostiantyn Bokhan, a technical lead at N-IX, focuses on data science projects. He leads data science projects in several areas: Computer vision, NLP, and signal processing as well as consults clients regarding digital transformations with AI. When free, he conducts research in the deep machine learning area. Kostiantyn has been an associate professor and faculty member of several universities since 2002. His research focuses on machine learning, deep learning, signal, and image processing. He received a PhD degree in network and telecommunications systems with research in digital signal processing in 2013. He has served on the scientific committees and review boards of several conferences. Speech Overview: Applying machine learning to make business applications and services intelligent is more than just training models and serving them. It requires implementing end-to-end and continuously repeatable cycles of training, testing, deploying, monitoring, and operating the models. Continuous delivery for machine learning (CD4ML) is a technique that enables reliable end-to-end cycles of development, deploying, and monitoring machine learning models. There are a lot of tools and frameworks that can be used to implement CD4ML. One of them is Kubeflow. Our experience of using Kubeflow for implementing CD4ML for the manufacturing area based on Azure Kubernetes service will be described in this speech.

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