Launch HN: AnswerGrid (YC S24) – Web research tool for lead generation

[tife]

Launch HN: AnswerGrid (YC S24) – Web research tool for lead generation

Hi HN! We’re Bolu and Noah from AnswerGrid (https://answergrid.ai). We’re building an AI-powered web research tool in the form of a spreadsheet. The problem we’re starting with is helping founders who sell to businesses discover the most relevant leads worth the investment of manual outbound (that is, worth putting in the effort to write a personalized outreach message to see if they might be interested).

There’s a demo video here: https://www.loom.com/share/fe4e40fa000b4406910a9ce247079138?..., and you can try the actual product at https://app.answergrid.ai/try-it (no signup needed!)

One of the biggest problems B2B founders have, once they’ve built an initial product, is finding initial companies to sell to. There’s a chicken-and-egg problem here: most companies don’t want to buy from a startup until it’s much further along, but the startup won’t get that far unless they find some customers. Locating those first companies who need what you’re building badly enough that they’ll go with you at an early stage is time-consuming and painful - you’re searching a haystack for a few needles. This is the problem we’re building software to help solve.

We found that for effective lead qualification—that is, narrowing down the haystack of potential companies to a few highly relevant ones—you can’t just search on keywords or industry categories like "AI," "Hardware," or "Healthcare" on other lead generation indexes. Those methods are too blunt to find adopters for an early product that almost necessarily has a narrow initial appeal.

Instead, you’d need to evaluate companies using many loose heuristics. For example, one of our early customers qualifies leads with questions like, "Do they offer subscription or usage-based pricing?" Most existing lead generation tools have forced founders to choose between thoughtful qualification research and increasing the reach of their high-quality outbound.

We found a few existing tools to wrangle CSV exports with additional AI qualifications, but nothing seemed built to help first-time founders like ourselves find the first couple of hyper-relevant companies to sell to. Their feature sets and advertised use cases (like "AI-written personalized messages") seemed optimized for scaling the go-to-market of a mature product—a completely different situation. This led us to focus on making lead gen intuitive for other builders selling for the first time, looking to find their early users.

We’ve built a tool to help founders codify the research heuristics they use to qualify leads that justify a time-consuming investment in human-written outreach. (Side note: while we’re using AI to help qualify leads, we emphatically do not want to help scale AI spam. Our tool aims to help you discover potential users worth writing to manually.)

Here’s how it works: Starting from lead-gen sources like Crunchbase, Apollo, and LinkedIn as a data foundation, we find leads that match a simple high-level company profile: “Series A Biotech startups in the US.” You can then further qualify leads using AI-powered tools such as (1) “web scrape,” which, when given a target URL column, spawns concurrent jobs to scrape (text and screenshots) the target sites of all companies in the table and returns LLM evaluations based on a prompt; and (2) “web search,” which returns answers and citations to natural language questions using information from the web.

These tools afford a greater level of expressiveness than simple keyword searches. We aspire for the tool to match the thoroughness a founder would apply manually on any given lead. But this time, help them do it for thousands of leads at a go.

Once you’ve narrowed prospects down with these granular qualifications, you can then use job descriptions to find the contact information of your potential customer champions.

While we’re excited about other web research use cases, we started with sales qualification because the research outcome is immediately actionable—" Who should I sell to today?"—and the feedback cycles are short—"Was that lead relevant?”.

We are exploring exposing our web research infrastructure through an API to other developers who'd find it helpful to enable web research workflows in their apps. Please reach out (https://tinyurl.com/AnswerGrid-15) if you’re working on a product that might benefit from this.

You can try the tool here: https://app.answergrid.ai/try-it (no signup needed)

We’re excited to hear about any lead qualification tricks you’ve discovered for identifying your early users or what other use cases you think are relevant here. Even if you’re not looking to do lead generation, any product feedback from playing with the demo would still be most appreciated.

* A Note on how the Search box works: It tries to infer the starting Crunchbase filter configs based on your query. If it doesn’t get the configs precisely, you can edit the inferred filters at the top left corner once the grid is loaded, or try starting with a more straightforward query before adding extra LLM qualification columns.

[adam]

Congratulations on the launch. We sell B2B crowd forecasting software, a fairly niche market, so something like this could be very interesting for us. We sell mostly into governments, think tanks, and other types of research institutions, with the occasional commercial application. A couple thoughts:

Perhaps I didn't do something correctly, but I ended up with a list of companies. That saves me a little time, but I want to be able to then get to something role-based. Is this behind the upgrade or do I never see this information?

Related, I want role to be one of my primary filtering mechanisms. Find me all Chief Risk Officers in x,y,z industry for companies larger than 500 people, for example. Then let me review their backgrounds, get their contact info, and contact them.

I think this is how many sales people / founders operate to try and start to sell. What am I missing?

[tife]

Yes! you can add contacts based on job description. You'd do that by clicking on the far-right of the table to add a column, then select "Find Employees" and add as many key words and job descriptions as are relevant.

Here's a list of Chief Risk officers for "Companies in the insurance industry with more than 500 employees": https://app.answergrid.ai/try-it?starting-grid=af8339c3-4619...

You can interact with the contact cards, by clicking and visiting their linkedin (we didn't expose emails on the demo, but those are available aswell)

[gargan]

Congratulations on the launch! I've done Python scripts to do this, which connect to APIs like Apollo, use proxies for Google scraping, and scraping libraries for URLs etc. It's no small feat to connect it all together. Your product looks next level, and with a gorgeous spreadsheet UI too. Very nice

[tife]

Thank you!

Are you still using your stack for outbound :) ?

[BrandiATMuhkuh]

Congratulations on the launch.

I was about to build something similar to help someone dear to me on their job hunt.

However, AnswerGrid looks very promising: https://app.answergrid.ai/try-it?starting-grid=9c5cf105-266e...

[tife]

Yes, we've been hearing a bit about the job search use case as well.

I'll add that you could add a column for (linkedin) job postings too :)

Here's the updated Grid: https://app.answergrid.ai/try-it?starting-grid=c4ad0d6c-2eca...

(Most of them didn't have postings though, so I put a filter on the column to limit to those that do)

[trevoragilbert]

Congrats on the launch. As someone who has dealt with early lead-gen at multiple startups, I'd say it's 50% finding the right company and 50% finding the right person at that company. Especially when there isn't already a network connection.

[tife]

Absolutely. Some users find that the person search component can be an additional layer when selling to larger enterprises with multiple decision-makers and budget holders. Deploying our tooling towards champion search within orgs is definitely on the radar as we look to help with that other 50% of the problem. Right now, users do that with just Job descriptions and keyword searches when adding a column for Employees.

[warthog]

How does this differ to a tool like Clay.com and their Claygent

[tife]

For lead generation, some users have found Clay to have a slightly steep learning curve, which makes sense if you were scaling GTM and want to set up elaborate waterfall mechanisms for contact enrichment.

So we built this to be walk-up usable for people doing sales for the first time and want to focus on precise qualification and not just scale of outreach

[sam_perez]

My first thought/question as well.

[altdataseller]

What happens when I download all the leads you give me? Why would i keep my subscription? Of course you might find new leads that fit my query, but that initial list is good enough for last for awhile to reach out to…

Also, does the scraping of the Linkedin profiles happen on my machine or your servers? If on mine, do I need a LI account? Do i need to be logged in?

[rawoke083600]

Congrats on launch !

We sell CMMS (Maintenance Software) for physical assets, "Corrective Maintenance" and "Planned Preventive Maintenance"

Our main clients are usually restaurants (KFC, JAVAHouse etc).

I did try a few queries to discover similar places:

* Companies with more than 10 physical branches like restaurants or banks (We don't yet support this query)

[handfuloflight]

Any interesting stories of you using your own tool to find customers for it?

[tife]

We had an early campaign where one of our AI columns was tasked with inferring the ICP of all companies based on their description.

We then used these ICPs to create a personalized starting list of leads for them.

This did not work very well, as most ICPs ended up looking as generic as "SaaS companies with more than 10 employees."

This was one of the reasons we decided that using AIs to write copy or create anything that would make it into the outbound itself was not the best use of their strengths.

Instead, the tools should be deployed towards qualification :)

[throw03172019]

Looks great! What about non-startup information? For example, if my company sells to Plumbing companies or roofing companies.

[tife]

Ah yes, for people trying to reach companies outside of the crunchase/linkedin/apollo universe, we would not be great for discovering them.

However, we've had users find leads from other SMB-focused indexes and import them as CSVs into AnswerGrid for additional research.

One example is if you had a list of thousands of roofing companies (with websites) and wanted to flag which of them focused on commercial projects. You'd import this list and deploy our web scraping tool to visit their websites and look for any indication of this.

We are, however, planning to expand the coverage of our company index too

[edg5000]

I recently had to do lead gen. I obtained a copy of the chamber of commerce database from my country; in the order of a million records. Then I wrote code to import that into an SQL database.

Before that I tried LinkedIn Sales Navigator, but it won't let you export, you have to use other paid tools to scape from your (paid) linkedin account. Buying data from a broker was 0.07 EUR/record, I found that too expensive since I have to do a bunch of filtering after I get the data.

In my scenario, I don't need emails, just business names filtered by industry, location and ideally size. I was able to find a local online phone book which had the amount of employees for each company. Scraping this was a pain and slow but it enriched the chamber of commerce data a bit.

After filtering, I start checking out each company's website. I use a graphical SQL DB viewer to mark qualified companies. I then proceed to email and call the companies. Using a graphical DB tool I keep notes and track the funnel state of each company, as well as enriching the data manually as I go (contact info and names mostly).

For countries where chamber of commerce data is not available freely, one can buy leads, based on some filters such as industry. I suppose that is the "traditional" industry you are competing with.

A thing your tool might be great at is the filtering stage, in my case I used the officially registered industries/categories. Companies are classified in a very detailed manner in my country, which helps a lot, but still some granularity is missing.

Being able to use keywords, that are not just used as fulltext search, but passed through an AI, will be valuable. Without AI this would be very hard to do. Google has mastered this, if there are synonyms for a word, Google will still find all results regardless of the term used. Probably your tool will be able to do the same now, thanks to AI.

Good luck with the business. It is an established industry, but probably plenty of room for innovation and competition.

[ckluis]

Don’t make me hunt for pricing! Looks great.

[tife]

Sorry about that!

We've found that there's some variance in the shape of workloads users have (some doing lead gen, so pricing per lead makes sense; and others uploading CSVs of their own leads and only want to use our AI research tooling, in which case usage-based pricing might be more appropriate), so we like to chat briefly to get a sense (at least until we figure out clean pricing tiers.)

Can you please book 15 minutes here to chat: https://tinyurl.com/AnswerGrid-15

[haliax]

Really cool, awesome work!

[rrr_oh_man]

> Thank you for your interest in AnswerGrid. Our app is best experienced on larger screens. Please access AnswerGrid from a desktop or tablet device.

Oh how much I hate this. Just let me browse at my own risk, ffs.

[ohnoah]

Thanks for the feedback. We hadn't anticipated anyone wanting to use the app on mobile since the app is designed primarily for larger screens. However, I just put up a patch which allows you to "Continue anyway" when faced with this warning message, which will allow you to test the app on on mobile should you wish!