1/ We redesigned our marketing home page and got 50% more clicks, and 20% more installs.
Want to learn how we did it? 🧵⬇️
2/ A picture is worth 1k words 🖼
Instead of lines of text telling people why to use #Neeva, we show them!
Our new website visualizes installing Neeva so they:
🅰️ Know what to expect
🅱️ Show them the benefits of tracker blocking 🛑 and address bar search 🔎
3/ Use your words wisely ✍️
We changed our headline to be more on brand and highlight the core value people get from Neeva.
No clever wording, just real tangible benefits.
4/ What were the results? 📈
🌟 More users download our chrome extension
🌟 More people engaged and gave us a try by running a search
🌟 A 50% increase in average searches/user
🌟 1.3X increase in 1 day active users
5/ We approach growth with hypotheses and experiments, so we can isolate what we want to change, and we can see the results clearly. Don’t throw too much into any 1 test, but also swing big (especially if you’re trying to grow as fast as we are).
6/ Have you tried these tactics? Any others you’d share? Let us know!
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1/ It's not the size, it's the skill - now releasing #Neeva's Query Embedding Model!
Our query embedding model beats @openai’s Curie which is orders of magnitude bigger and 100000x more expensive. 🤯
Keep reading to find out how... 📖
2/ Query understanding is the life blood of #searchengines. Large search engines spent millions of SWE hours building various signals like synonymy, spelling, term weighting, compounds, etc.
3/ We solve the problem of #query similarity: when 2 user queries looking for the same information on the web.
Why is this useful? Query-click data for web docs = strongest signal for search, QA, etc.; solving query equivalence => smear click signal over lots of user queries
1/ Google will do just about anything to maintain its monopoly power
Fear-inducing pop-ups with misleading designs to trick users into going back to Google search ✅
What’s a competing search engine to do? The only thing we can…Design and innovate our way out of it! 🧵
2/ By default, Google Chrome comes with Google search – no surprise there.
However, if a user prefers a more privacy focused search engine, they have to jump through a few hoops to install an extension and make it as the default.
All in all not terribly difficult so far, but…
3/ The last thing Google wants is to lose a user, especially from their cash cow – search.
So, under the guise of security, upon installing a new search extension such as Neeva and attempting your first search from the omnibar, they deploy the misleading warning prompt.
1/ When someone types “neeva” into search, how do we know they mean “neeva.com” instead of “neevaneevaneeva.com”? After all, the second has 3 times as much neeva!
See how you can do much better than vanilla TF-IDF / cosine similarity for textual relevance!🧵
2/ Textual relevance is only one part of document ranking (alongside signals like centrality, page quality, and click rate)
But it’s one the most important parts and the one we’ll be covering in today’s thread.
3/ The most popular way to rank documents relative to queries is to use TF-IDF vector representation.
Essentially, this claims the more often a term occurs on a page (TF), and the less often it occurs on other pages (IDF) the more likely that term is to be relevant to the page.
(3/) Building a comprehensive index of the web is a prerequisite to competing in search. First step for Neeva search engine is “downloading the Internet” via Neeva’s crawler (Neevabot)
However, many sites only allow Google and Microsoft unfettered access to crawl/collect info