Neeva Profile picture
Jan 18 13 tweets 6 min read
1/ At #Neeva, design is the act of giving form to an idea: we gather data and inspiration, think, make, and iterate through feedback. 💡

Here's how our team, working alongside the ✨Neeva Community✨, shaped our latest news tool, #BiasBuster...

(read on 📖)
2/ To improve the news experience on Neeva, we solicited insights from users of various news outlets.

One early finding 👉 the journey to get daily news typically started from news providers' sites and apps, but NOT from a search engine.

🤔
3/ So we asked ourselves, when does a search engine becomes necessary and helpful in the journey? 💭

Several users shared that they searched for specific events and stories about which they wanted to learn more.

An avid news user put, "Search is for focused topics.".
4/ The users visited their typical news providers' services to get daily news. But where did they go to get more points of view, especially for political news?

Some said their news sources were sufficient. ✔️

Some went out to check opposing views from the sources they knew. 👀
5/ Checking POVs by visiting multiple outlets takes a LOT of effort.

But do you know who’s capable of making this process effortless? Neeva! 🦸

We pursued the idea. 🧠
6/ Limited sources and freshness were common complaints about news on search engines. Quick retrieval of POVs from broad & fresh sources was also crucial.

The critical aspects of our backend and frontend to rally around were:
✨Broad✨
✨Fresh✨
✨Fast✨
✨Easy✨
7/ Going into detail design development, we generated ideas to express that this tool was about finding and viewing news articles in the spectrum.

Here are ideas we came up with ⬇️
8/ We struggled to find ways to signal and invite the user to drag the control around to set the desired position. 😑

Our caring Neeva Makers community unblocked us with detailed feedback.

Thank you Makers for helping us all along throughout the process! 💓
9/ We investigated UI motions to visually explain news source changes. Also, the motion exercise using the @Framer Motion, an animation library, answered our pathway for UI implementation.
10/ We chose the seesaw figure with color gradients.

We rotated the half-circle within a rectangular container as a mask because it was:
✅ Sufficient enough to express the POV selection
✅ Practical to implement

We prototyped in @principleapp + gathered usability issues.
11/ When an end-to-end build was ready, 80+ opted-in users shared candid critiques.

This sped up the backend improvements & UI polishes:
📌 Wider handle
📌 Clarity on what range is selected
📌 Hover tilt in a randomized direction
📌 Handle dot color changes for a bit of fun
12/ After many meetings, @clickup tickets, and a lot of math, we refined other details, like snapping the thumb to the nearest point on the spectrum and rubber-banding on the edges.

And we shipped in the US just in time for the midterm elections in November. 🙌
13/ What's next? Users shared:
🗣️ Bias Buster can help them relate better to their friends' perspectives
🗣️ Neeva should build an AI summary of opinions

So, the fun of making a better news experience will continue... 😄

Bias Buster is available now at neeva.com!

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Neeva

Neeva Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @Neeva

Jan 17
1/ Have you heard? Bias Buster is now available in #Neeva's main search tab!

🔎 Try a search here: neeva.com/search?q=calif…

And if you're wondering how we crawled and evaluated topics to create our 5 point scale slider, stay tuned! 🤓

We dive into it on this thread 🧵… Image
2/ Our goal? 👉 Show a variety of POVs on particular news topics.

To reach this goal, we categorized results based on 5 buckets to ensure a smooth experience while interacting with the slider. This includes:

🪣 Far Left
🪣 Left Leaning
🪣 Center
🪣 Right Leaning
🪣 Far Right
3/ So, how do we categorize our results to fit these buckets?

By using third party media bias tools, such as @AllSidesNow and @MBFC_News.

Each result is categorized by its respective domain.
Read 11 tweets
Oct 10, 2022
1/ We redesigned our marketing home page and got 50% more clicks, and 20% more installs.

Want to learn how we did it? 🧵⬇️ Image
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.
Read 6 tweets
Sep 23, 2022
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.

We don’t have that luxury. 🙄

Fortunately for us, #LLMs are here to build upon.
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
Read 10 tweets
Jul 7, 2022
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.
Read 16 tweets
Jul 5, 2022
(1/) You know the drill. Head to a website, and get hit with a pop up asking to enable cookies.

Too often we just click “accept all” to get rid of the prompt, privacy be damned

Rather than 🤷‍♀️, we set out to get rid of these annoying banners & keeping your privacy intact.

🧵
(2/) Why should you care about cookies?

Sites save these small text files on your device and use them to track you.

Little crumbs that track sites you visit, what you shop for, and even what you search for.

That private & valuable info is sold and ads are targeted back at you.
(3/) Targeted ads make our skin crawl at Neeva, so we built Cookie Cutter to kick these invasive cookies to the curb.

So why not just block all cookies?

Unfortunately it’s not so easy, sites have to use some cookies, for example, to log you in or remember your shopping cart.
Read 14 tweets
Jun 7, 2022
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.
Read 16 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us on Twitter!

:(