Honestly - See what Reddit and TikTok honestly think about your product
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As bots and AI agents overrun the internet, finding real customer opinions is only getting harder. Honestly cuts through the chaos by discovering verified conversations about your product across Reddit, TikTok, X, YouTube, Instagram, & Facebook then turning them into insights your team can act on.
Replies
Great work! Honestly seems like it is primarily geared towards larger companies since a demo is required to move forward with the platform. However, we are a small team. Do you have any self-service options for startups or small teams? The competitive analysis features seems compelling our this category of clients.
Honestly
@hoa_do_012 Thanks for your question! We serve both larger enterprises and early stage startups. We currently have a self-service option for startups/smaller teams on the roadmap, but for now are meeting with each customer to ensure we meet their needs since the insights businesses require varies based on the stage they are in as well as the industry. Competitive analysis has been one of the most popular services for our smaller team clients so far. Beyond competitive analysis, is there another type of insight you'd like to see in the self-serve version of Honestly?
Honestly
@hoa_do_012 Self service is coming real soon 👀
@scott_davidson_jr Reddit is really hard to handle while posting self promotion related to companies, Will your product help to do that strategically ?
Honestly
@harini_mukesh Thanks for the question Harini! Yes, we are able to strategically determine the validity of these posts. I know this is a common issue many users and companies run into, but our algorithms have been doing a great job and weeding out the the sponsored posts that try to disguise themselves as organic. Have you experienced this issue outside Reddit as well?
Honestly
@harini_mukesh In that case I'd definitely encourage you to make use of the 7 day free trial we offer to see how it performs for your brand!
@scott_davidson_jr Sure that would be awesome, will try and share my experience... Thanks!!!
Voquill
This looks useful, especially now that it's getting harder to separate real customer feedback from AI-generated noise. How do you verify that a conversation is authentic, and what signals do you use to filter out fake engagement? Congrats on the launch!
Honestly
@henry_habib Thank you and this is exactly why we started Honestly, to combat this very problem! For detecting whether or not a post is AI generated, we have internal tooling combined with partnerships with leading AI detection models for image, video, audio, and text detection i.e. CheckReality.ai. On top of that authentic vs. sponsored content is determined by various signals about the post such as any listing of sponsorship tags, image or video abnormalities, the structure of the text, etc. As for specific engagement, we are able to analyze the account's history with posts, views, likes, and other factors to evaluate the engagement effectively. What platforms have you had the most issues with fake engagement if you don't mind me asking?
Honestly
@henry_habib Thank you!!
This is really interesting — the AI detection angle is what stands out to me. How accurate is the verification layer when it comes to short-form content like TikTok comments where tone is really hard to read even for humans?
Honestly
@doganakbulut That is what we've been told! The verification layer is highly accurate with these comments that reach a certain threshold of length. If it is under the threshold, it might be more difficult to analyze but at that point the comment is not valuable enough to even be analyzed. The TikTok comment interest is very intriguing, wondering where the value is in this specific type of social media content for your team?
The Reddit + TikTok combo is the right pick — those two are where "what people actually think" lives, vs the polished stuff on X/LinkedIn. Curious how it handles small/new products with low mention volume — does it surface a single thread or does it need a baseline?
Honestly
@felix_masera Agreed - this mix of platforms is very all encompassing in terms of what type of data and industries are represented. X & LinkedIn is polished for sure but can still be valuable depending on the use case for one's business. With small/new products, if it has publicly available data online, we find it. However if there is insufficient data to draw real meaning or insights about customers, many our of clients resort to competitive analysis on other products that are more data rich for insights on their market. Is low mention volume currently something you encounter? If so, have you considered analyzing competitor data for valuable market information?
It's really an interesting idea. There is so much customer feedback spread across different platforms now, but actually finding what is real and useful is becoming harder, I saw the other day about an influencer talking about the dead internet theory and how it's full of bots and AI generated stuff. I can see how this could help teams save a lot of time. Curious, how do you decide which conversations are trustworthy enough to include in the insights?
Honestly
@reda_roqai_chaoui Agreed! The general idea we’re going for is seen as an “inevitable issue” because no one wants to live in a world where the dead internet theory is a reality.
We don’t believe in censoring posts, just truthfully tagging them. Clients who are in the affiliate marketing space actually filter specifically for sponsored posts as an example for competitor research in their insight reports!
The gap between what consumers say in a formal research setting and what they actually think is one of the most underrated problems in brand strategy. Reddit and TikTok are genuinely where unfiltered consumer truth lives - this is an interesting angle on that. Curious how you handle conflicting signals when Reddit and TikTok audiences have very different takes on the same product?
Honestly
@productrambler Thanks for your very thoughtful comment & question Lava! This specific question would be an instance of a valuable insight our reporting would highlight because it emphasizes that there is one type of audience that is favorable to the product and the other dislikes it. This shows both an opportunity for marketing where engagement will be high as well as an area of customer research as to why a certain platform as the opposite opinion of another. How often have you come across these types of situations and how have you/your team interpreted them in the past?
the bot/fake review problem on social is so bad right now that "verified authentic" is doing a lot of heavy lifting here. curious how you handle edge cases where someone posts about your product without naming it directly (like describing a feature or a bug). does Honestly still pick those up?
Honestly
@rnagulapalle It really is! As for your question, yes when someone posts about specific aspects of a product it is very dependent on how it is described. For example, it a user complains about a "bug with an API key" but no other information about the product responsible for the error, Honestly analyzes the context of the post - the account name, and forum post title, and other comments connected to the quote.
@scott_davidson_jr that context-graph approach makes sense actually. the hard part with indirect mentions is that the signal is spread across multiple posts/threads and easy to miss manually. good to know Honestly is stitching those together. does it weight mentions differently based on how close the context match is, or is it more binary (found / not found)?
Honestly
@rnagulapalle It currently is binary but we are planning to test how much more effective the approach is when different weights are applied based context closeness match. Great additional question!
EverTutor AI
From my experience with scraping, dealing with social media platforms can be very challenging as they constantly switch their algorithms up and actively try to prevent scraping from occurring. Is this an issue for Honestly at all? If so, is it impacting how you get data and the amount that you get?
Honestly
@suryansh_tiwari2 Completely valid question and although it is a challenge, it has been one we have been able to overcome. The internal methods we utilize as well as the engineers that keep up with the changes from these algorithms have been able to effectively retrieve product data across all the platforms we currently work with. There may be a slight time delay in bringing our algorithms for data retrieval up to speed but it has never been an obstacle in delivering the insights our customers need.
Curious about your background in scraping - are there certain platforms you have seen that are more difficult to retrieve data from than others? If so, how did you deal with that in the past?
I like that Honestly looks at what people say when they are not filling out a survey. Reddit and TikTok conversations can be messy, but that mess is often where the most useful brand insights actually show up.
Honestly
@albion_idrizi For sure! The surveys always have some level of bias to them (volunteer bias being the big one) which clouds the valuable insights you can draw from them. That's where social media conversations are most vital, especially after cleaning them up! Out of curiosity, how have you had to deal with these messy conversations in the past?