AI-Powered Product Discovery for Ecommerce: Guide

min. read

December 24, 2024

AI-Powered Product Discovery for Ecommerce: Guide

AI is transforming online shopping, making it easier for customers to find products and boosting sales for businesses. Here's what you need to know:

AI analyzes customer behavior, purchase history, and search patterns
It personalizes the shopping experience and improves search results
By 2025, AI could handle 95% of customer interactions in online shopping

Key benefits:

For Businesses	For Shoppers
Increased sales	Faster product finding
Better customer retention	Personalized recommendations
Optimized inventory	Easier discovery of new products

Main types of AI product discovery:

Collaborative filtering
Content-based filtering
Hybrid filtering

To implement AI-powered product discovery:

Choose the right system for your needs
Prepare your data (customer behavior, purchases, etc.)
Set up the system (often through an app or plugin)
Customize recommendations
Continuously test and improve

Multi-format search options:

Text
Voice
Image
Video

Remember: Good data is crucial. Keep it clean, updated, and protect customer privacy.

Measure success by tracking:

Conversion rates
Average order value
Customer lifetime value
Return on ad spend
Shopping cart abandonment rate

AI in e-commerce is growing fast. Stay informed and adapt to keep your competitive edge.

Basics of AI-Powered Product Discovery

AI is reshaping online shopping. It's making product discovery a breeze for customers and boosting sales for businesses.

Main Parts of AI Product Discovery

AI product discovery systems have four key components:

Data Analysis: Tracks customer behavior, purchase history, and search patterns
Machine Learning: Improves with each interaction
Personalization: Tailors the shopping experience
Smart Search: Understands intent, not just keywords

Advantages for Businesses and Shoppers

Businesses	Shoppers
Increased sales	Faster product finding
Customer retention	Custom recommendations
Optimized inventory	New product discovery

Real-world examples:

1. Amazon's AI Recommendations

Amazon's AI suggestions drive 35% of their sales. That's huge.

2. Sephora's Smart Beauty Picks

Sephora uses AI to match customers with the right beauty products based on skin type and past purchases.

3. Spotify's Music Discovery

Spotify users have spent over 2.3 billion hours listening to AI-created playlists.

"AI is the architect of a new, personalized e-commerce experience." - Industry Expert

By 2025, AI might handle 95% of customer interactions in online shopping. That's a big shift.

For businesses considering AI product discovery:

Start with quality data
Continuously test and improve
Prioritize customer privacy

AI-powered product discovery is a win-win, improving the shopping experience and driving business growth.

Setting Up AI Product Recommendations

AI product recommendations can boost your sales and make customers happier. Here's how to set them up:

Types of Recommendation Systems

There are three main types:

Collaborative Filtering: Groups users with similar interests
Content-Based Filtering: Suggests products based on features
Hybrid Filtering: Combines both for better accuracy

Netflix uses collaborative filtering for 75% of what people watch. It works.

Adding AI Recommendations

1. Pick the Right System

Choose one that fits your needs. Look at:

What it recommends
How good the suggestions are
What data it gives you
If it works with your store
The price

2. Get Your Data Ready

Collect info on:

What customers buy
How they browse
What they click on
Who they are

3. Set It Up

For most stores, it's as easy as adding an app. Try:

You'll usually just add a bit of code to your site.

4. Make It Your Own

Customize your recommendations. Here are some options:

Type	What It Does
AI-driven conversions	Shows stuff people are likely to buy
Similar items	Suggests based on product details
Recently viewed	Shows what the customer looked at before
Bestsellers	Promotes popular items to new visitors

5. Test and Improve

Keep testing different strategies. Watch:

How many product pages people view
How long they stay on your site
If they leave right away
How much they spend
If your sales go up

Using Multi-Format Search

Multi-format search is changing how people shop online. It's not just about typing anymore. Now, you can use images, voice, and more to find what you want.

What is Multi-Format Search?

It's a mix of different ways to search:

Text: Type what you want
Voice: Speak to search
Image: Use pictures to find similar stuff
Video: Find products from videos

This combo makes shopping feel more natural and easy.

Real-World Examples

Big players are already on board:

1. eBay's Image Search

Can't describe it? Just snap a pic:

Take a photo
Upload to eBay
Get matching products

Perfect for those "I want something like this" moments.

2. Amazon's Voice Shopping

Alexa, make shopping easier:

Say what you need
Alexa suggests based on your history
Confirm with your voice

Great for restocking your usual items without lifting a finger.

3. Walmart + Google Team-Up

They're offering:

Voice shopping lists
Text searches
Add-to-cart by voice

More ways to shop = happier customers.

Why It's a Game-Changer

For Shoppers	For Businesses
Find stuff faster	Sell more, faster
Get what you actually want	Fewer returns
Shop your way	Happier customers
More fun, less frustration	People stick around longer

The Numbers Don't Lie

142 million people use voice search
33.2 million in the U.S. have bought by voice
Visual search can get you to checkout 2x faster than text

Want to Add Multi-Format Search?

Pick one new format to start (like image search)
Clean up your product data
Test with real shoppers before going live
Keep tweaking based on how people use it

Multi-format search isn't just a fancy add-on. It's becoming the new normal for online shopping. By making it easier for people to find what they want, you're not just keeping up with trends – you're giving shoppers a reason to choose you over the competition.

Improving Product Discovery with AI

AI is revolutionizing online shopping. It's making product discovery a breeze for customers and boosting sales for businesses.

Making Search Results Personal

AI analyzes your shopping history, clicks, and behavior to serve up products you're more likely to love.

Here's the gist:

It checks what you've bought and searched for
Learns your preferences
Shows you products that match your taste

This personalization packs a punch. Puma saw a 52% sales boost using Klevu's AI search tool.

But it's not just about product recommendations. AI also:

Fixes your typos
Gets what you mean, even with different words
Highlights in-stock, ready-to-ship items

Adding Smart Visual Search

Ever seen something cool but didn't know what it's called? Enter visual search.

It lets you:

Snap a pic of an item you like
Upload it to a store's site or app
Find matching or similar products to buy

Big players are already on board:

eBay: Find items from photos
Amazon: Discover products through their app's camera

Why's this a game-changer? It works. CCC Group, a major shoe retailer, saw:

4x more purchases after visual search use
More items in carts
Happier customers overall

Michal Pachnik from CCC Group said: "The tool is changing the way people interact with e-commerce."

Quick comparison of visual and text search:

Feature	Visual Search	Text Search
Speed	2x faster item discovery	Slower
Accuracy	Exact matches	May miss similar items
Ease of Use	Just snap a pic	Requires product names

To nail visual search for your store:

1. Use high-quality product photos

2. Keep product data clean and updated

3. Test with real users before launch

4. Continuously improve based on user behavior

Tips for AI-Powered Product Discovery

Keeping Data Good and Private

Good data is key for AI product discovery. Here's how to keep your system running well:

Clean your data often
Update product details
Protect customer info

Mastercard's Shopping Muse shows what good data can do. It turns phrases like "beach formal" into product ideas based on user profiles.

Testing and Checking Performance

Make sure your AI system works:

1. Set clear goals

Amazon saw 35% more purchases from AI recommendations. Set similar targets for your store.

2. Use A/B testing

Test	Option A	Option B	Result
Algorithm	Collaborative filtering	Content-based filtering	A: 12% more clicks
Placement	Product page	Homepage	B: 8% higher conversion

3. Watch key metrics

Keep an eye on page views, time on site, bounce rate, email CTR, AOV, and sales uplift.

4. Ask users

Get feedback on product recommendations.

5. Check for bias

Make sure your AI isn't unfairly favoring certain products.

Keep improving. Puma boosted conversions by 52% with Klevu's AI search tool. But they didn't stop there – they kept making it better based on data.

Checking Results and Return on Investment

Want to know if AI product discovery is working for your e-commerce store? Here's how to measure its success:

Key Metrics to Track

Focus on these numbers:

Conversion Rate: How many visitors buy after seeing AI recommendations?
Average Order Value (AOV): Are people spending more with AI suggestions?
Customer Lifetime Value (CLTV): Does AI keep customers coming back?
Return on Ad Spend (ROAS): Is AI making your marketing more efficient?
Shopping Cart Abandonment Rate: Does AI help close more sales?

Metric	How to Calculate	What You Want
Conversion Rate	(Conversions ÷ Visitors) x 100	Up
AOV	Total Revenue / Total Orders	Up
CLTV	AOV x Orders per Customer x Customer Lifetime	Up
ROAS	Total Sales / Total Ad Spend	Up
Cart Abandonment	(Sales ÷ Carts) x 100	Down

Measuring Impact on Sales and Customer Behavior

To see how AI affects your store:

Record your numbers before AI
Compare AI pages vs. non-AI pages
Look at how long people stay and how many pages they visit
Check search patterns and click rates
Ask customers what they think

AI can do more than just boost sales. Microsoft found that 72% of Copilot users felt less stressed doing routine tasks.

To figure out AI ROI, use this:

ROI = (Net Profit from AI / Cost of AI Investment) x 100

But remember, AI's value isn't always direct. McKinsey thinks generative AI could add $2.6-$4.4 trillion to global productivity. Look at things like customer happiness and efficiency gains to see AI's full impact.

Solving Common Problems

AI product discovery in e-commerce can be tricky. Here are some key issues and fixes:

Common Mistakes and How to Avoid Them

1. Rushing to solutions

Teams often spend 80% of their time on solutions and only 20% on understanding problems. This leads to products that miss the mark.

Fix: Aim for a 50-50 split between problem and solution. Dig deeper into user issues before jumping to answers.

2. Ignoring stakeholders

Leaving out key people can mean missed insights and market misalignment.

Fix: Include stakeholders throughout. At productboard, they use three main check-ins:

Framing the problem
Solution brainstorming
Delivery planning

3. Late engineer involvement

Not bringing in tech experts early can lead to unrealistic solutions.

Fix: Include at least one engineer from the start. As Marty Cagan says:

"If you're just using your engineers to code, you're only getting about half their value."

4. Fragmented tools

Using multiple vendors for different features can be costly and complex.

Fix: Look for integrated solutions that combine visual, text, and filter search. It's simpler and smoother for users.

5. Overlooking bias

AI can perpetuate discrimination if not carefully designed.

Fix:

Use diverse data sets
Implement bias-aware algorithms
Create diverse AI development teams

Strategy	Description
Inclusive Data	Gather data from underrepresented groups
Bias-Aware Algorithms	Design to detect and reduce bias
Diverse AI Teams	Include varied backgrounds and skills

Building Trust

Customers are wary of AI. A Salesforce study found that while 76% trust companies to make honest product claims, only 57% trust them to use AI ethically.

To build trust:

Be clear: Explain how you use AI and data. 89% of customers want to know when they're talking to AI vs. humans.
Human oversight: 80% say it's important for humans to check AI outputs.
Address concerns: 63% worry about AI bias. Show how you're tackling this.
Show benefits: Demonstrate how AI improves shopping. ASOS saw a 50% drop in failed searches after upgrading their search engine.
Give control: Let customers opt in or out of AI features.

What's Next for AI Product Discovery

AI's changing e-commerce. Here's what's coming:

New Tech on the Horizon

1. Generative AI Goes Mainstream

Apple's iPhone 16 will use generative AI for "Apple Intelligence". This shows AI moving into our pockets, changing how we shop online.

2. Voice Shopping Boom

Voice shopping's exploding. It jumped from $2 billion in 2017 to $40 billion in 2022. Get ready for more voice assistants helping you shop.

3. AR and VR Shopping

By 2025, AR and VR will shake up online shopping. Picture seeing furniture in your room before buying.

4. AI Creating Products

AI's not just finding products; it's making them. eBay now uses AI to write product descriptions from photos. Sellers can list items faster.

Preparing for the Future

To stay ahead:

1. Get AI Tools

Pick AI solutions that fit your needs. Look for platforms with both product discovery and marketing features.

2. Clean Up Your Data

AI needs good data. Set up solid data collection processes.

3. Jump into Social Commerce

Social media's becoming a shopping hub. Instagram and TikTok now let users buy without leaving the app.

4. Personalize Everything

Use AI to tailor shopping for each customer. It boosts satisfaction and sales.

5. Keep Learning

AI in e-commerce never stops evolving. Stay informed to keep your edge.

AI Trend	E-commerce Impact
Generative AI	Makes product descriptions, personalizes content
Voice Shopping	Enables hands-free buying
AR/VR	Lets customers try before they buy
Social Commerce	Turns social platforms into shops
AI Personalization	Tailors recommendations for each shopper

Conclusion

AI is shaking up e-commerce. It's making shopping a breeze and pumping up sales.

Here's the scoop:

Customers find stuff faster
They get personalized picks
Companies see big wins in sales and happy customers

Take MISUMI USA. They slapped on AI search and BAM! 80% more conversions. And McKinsey? They say AI personalization can juice up revenue by 10-30%.

What's cooking? AI in e-commerce is on fire. By 2030, we're talking a $16.8 billion market for AI e-commerce tools.

Want to stay in the game?

1. Jump on AI now. Pick tools that fit your shop.

2. Data is king. Feed your AI good stuff.

3. Keep your eyes peeled. AI moves fast.

Here's the kicker: AI isn't just for the big dogs anymore. It's getting cheaper and easier to use. Even the little guys can get in on the action.

AI-Powered Product Discovery for Ecommerce: Guide