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A Comprehensive Digital Sales Room Platform for B2B Sales Teams

Hacker News

A Comprehensive Digital Sales Room Platform for B2B Sales Teams

Hi HN, We are building a digital sales room platform for B2B Sales Teams and would love to get this community in our early access list. Some Context: If you are selling to B2B / Enterprise, you will be able to relate to some of these challenges: 1. The prospect needs a product presentation - which one should you send?? 2. Comments from prospects like: “We are reviewing internally” - well, are they really reviewing?? 3. Questions you ask yourselves like: "When and how should I follow up with this deal?”; “Is this deal going to convert this quarter?” …and so much more uncertainty. We’ve felt these challenges ourselves and thus decided to build Dealintent - an exciting product to help B2B sales teams identify, engage, and convert high-intent buyers while making the decision-making process easier for the buyers. With our product Dealintent, sales teams can use AI powered personality insights to uncover their buyers’ persona, quickly consolidate and share personalized content, and add stakeholders in digital sales rooms, streamlining the sales process and increasing efficiency. If you’ve like to check out a quick walkthrough, you can simply watch the demo here: https://vimeo.com/788566472 We are currently running an early access campaign and giving out a 50% off on both our solo and team plans (in addition to a few more exciting offers to our early set of users). Click here to sign up for our early access campaign - https://www.dealintent.com/early-access?utm_source=HN&utm_medium=HN_post&utm_campaign=HN_Early_Access We are also hoping that some of you might have inputs and suggestions, so please send them our way. If you have any questions, please do let us know as well - we'll gladly answer as best as we can. Look forward to it HN!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
89%89% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, context · Missing: mac, agents, macos
74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, users, way · Missing: mobile apps, ios, entrepreneurs
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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