Huge volumes of fake online validation signals (reviews, ratings, likes, comments, views … ) have eroded the Digital Trust. We need personalized network powered online validation signals. Huge volumes of fake online validation signals (reviews, ratings, likes, comments, views … ) have eroded the Digital Trust. We need personalized network powered online validation signals. Huge volumes of fake online validation signals (reviews, ratings, likes, comments, views … ) have eroded the Digital Trust. We need personalized network powered online validation signals. Huge volumes of fake online validation signals (reviews, ratings, likes, comments, views … ) have eroded the Digital Trust. We need personalized network powered online validation signals. As a product person building B2C and B2B digital products for over a decade I think the online ratings and reviews have become increasingly meaningless and are nearing their end of life. I spend hours examining ratings, reviews of a product or service with 4.5+ stars, 100s of positive review comments and even watch a bunch of influencers hyping it before hitting ‘BUY’. Only to be disappointed. I am sure you have faced this too. I call this the digital Trust Crisis. Reviews Were Meant To Help Us Decide, Isn't It? From deciding on the restaurants to buying high value items like electronics or selecting a vacation destination/rentals, we have all relied on these reviews and ratings. These helped us in making the final leap of confidence to buy. A decade or two ago our validation signals were mostly from the TV, newspapers and other physical ads to build enough trust to buy. These have now been augmented heavily by the online validation signals such as reviews, ratings, likes, comments, views and similar. While this has enabled democratizing the ability to share our views and influence others, it has also created overwhelming amounts of deception. Reality Is That This Deceptive Trust Is Cheap The Internet has overwhelming amounts of these fake validation signals. Likes and comments are bought for pennies, views and reviews written by clickfarm workers. Adding to this are the synthetic AI generated contents mimicking real users which are getting increasingly difficult to distinguish. Reality is that some companies are ending up buying these fake validation signals to build their brands. Even worse, some businesses even attack competitors with fake 1 star reviews damaging their reputation. I have used many tools to filter these out both for personal and at work for our customers but the harsh reality is these platforms are at a losing war. Fake validation signals are becoming increasingly indistinguishable. fake validation signals fake validation signals We End Up Paying For All The Cost Of Fake Validation Signals I have been there, most likely you too have! You read the rave reviews, watch the influencers and hit “BUY NOW” with confidence. What arrives then is nothing like it was promised. Buyer’s remorse in its rawest form, it is painful. We are not alone, this is happening millions of times a day. All of us the Buyers, Sellers, Suppliers, Businesses and the Platforms LOSE. I think these Fake Validations/Trust has rippling effect, here are some things I faced personally and professionally Time - it drains all my precious time spent in researching and ends with disappointment


Energy - I endlessly scroll and compare to find the best but end up mentally burned out


Good ones are lost - great products are buried in the mountains of fake praises for the inferior


Costs to Business - Our cost of running the business increased due to high return rates, frustrated customers, overloaded support teams and stressed our supply chain operations. Eventually, in order to deal with all these additional costs, I had to increase the cost of the product for our customers. This led to more unhappy customers, a vicious cycle.
The bigger picture is that this Trust Erosion is not just affecting my products and customers. It is chipping away at the entire market rapidly. Hence, my solution ‘Smarter Trusted Signals’ Time - it drains all my precious time spent in researching and ends with disappointment Time - it drains all my precious time spent in researching and ends with disappointment Time Time Energy - I endlessly scroll and compare to find the best but end up mentally burned out Energy - I endlessly scroll and compare to find the best but end up mentally burned out Energy Energy Good ones are lost - great products are buried in the mountains of fake praises for the inferior Good ones are lost - great products are buried in the mountains of fake praises for the inferior Good ones are lost Good ones are lost Costs to Business - Our cost of running the business increased due to high return rates, frustrated customers, overloaded support teams and stressed our supply chain operations. Eventually, in order to deal with all these additional costs, I had to increase the cost of the product for our customers. This led to more unhappy customers, a vicious cycle.
The bigger picture is that this Trust Erosion is not just affecting my products and customers. It is chipping away at the entire market rapidly. Hence, my solution ‘Smarter Trusted Signals’ Costs to Business - Our cost of running the business increased due to high return rates, frustrated customers, overloaded support teams and stressed our supply chain operations. Eventually, in order to deal with all these additional costs, I had to increase the cost of the product for our customers. This led to more unhappy customers, a vicious cycle. Costs to Business Costs to Business The bigger picture is that this Trust Erosion is not just affecting my products and customers. It is chipping away at the entire market rapidly. Hence, my solution ‘Smarter Trusted Signals’ Trust Erosion my solution ‘Smarter Trusted Signals’ ‘Smarter Trusted Signals’ ‘Smarter Trusted Signals’ Solution: Smarter Trusted Signals I was thinking, how would it be if reviews weren’t from strangers but from people I know. It all started when I imagined seeing the Rating of restaurants only from people I know or from my network. Our 1st degree network (family and friends), 2nd degree network (friends of friends), 3rd degree network (people I don’t personally know but have similar tastes and behaviors as me) can help in developing a Network Proximity Score. This can enable us in filtering Validation Signals from actual people from our network who we know and who are contextually closer to us. We Already Have The Infrastructure To Build This Product My inspiration to create this product comes from Google Maps which offers a 101 level preview of how this works. You might have noticed “80% match” for a restaurant. This is actually a behavior based matching. My research in the idea of human connectedness led me to the "Small World experiment by Stanley Milgram in 1967". He proved this through the “Six degrees of separation" or “six handshake” rule that any two people on earth are only six or fewer social connections apart. This means if I shake hands with 30 people and each of them shakes hands with another 30 and so on for six steps, I could connect with everyone in this world. "Small World experiment by Stanley Milgram in 1967" "Small World experiment by Stanley Milgram in 1967" two people on earth are only six or fewer social connections two people on earth are only six or fewer social connections My search further led me to "Meta’s social graph research in 2016" which states it is not Six degrees of separation anymore and it is only 3.5 degrees of separation now. I think this is a huge opportunity. If I can tap into my 1st, 2nd and 3rd network circles we can filter the most relevant ratings and reviews which is our “Trusted Signal” cutting out all other noise and fakes. "Meta’s social graph research in 2016" "Meta’s social graph research in 2016" only 3.5 degrees of separation now only 3.5 degrees of separation now My Vision is to rebuild The Trust On Validation Signals I want to build digital credibility ground up restoring the Trust on the Validation Signals (ratings, reviews, likes, views), the way it is meant to be. Showing only the reviews from trusted circles using network proximity scoring. Giving the users the power to make the right choices through “Smarter Trusted Signals”. Letting the users toggle between mass opinion vs. trusted circles. By building this product I think we can Improve customer satisfaction, reduce returns there by reducing the cost of supply operations and customer care operations and significantly kill the fake validation signals. build digital credibility ground up restoring the Trust build digital credibility ground up restoring the Trust Conclusion Thereby enabling great products and services to rise and shady ones fail themselves. Please don’t think of this as just a new review system. I think this will be the foundation of the next evolution of the Internet. We just went by the likes and reviews for too long. It's high time for this “Smarter Trusted Signals". Lets leverage AI to rebuild digital credibility with Trusted Validation Signals and puts human connectedness first.  Want to join me in redefining trust? Lets talk, because I think the next wave of the internet belongs to those who will rebuild its credibility. the foundation of the next evolution of the Internet the foundation of the next evolution of the Internet next wave of the internet belongs to those who will rebuild its credibility.

Online Ratings And Reviews Have Lost Trust, My View As A Product Person

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