Skip to main contentSkip to footer

Product Recommendation Chatbot

A guided shopping assistant that asks a few simple questions and suggests the right products from your catalogue, helping shoppers decide faster and reducing abandoned browsing.

Too Many Choices Stop Shoppers From Buying

A store with hundreds of products can overwhelm shoppers. Someone looking for a gift, a laptop for study, a skincare routine for oily skin or a sofa for a small flat does not want to open fifty product pages and compare specifications. In a physical shop, a good salesperson asks a few questions and brings out two or three suitable options. Online, most stores leave visitors to work it out for themselves, and many leave without buying.

A product recommendation chatbot plays the role of that salesperson. It starts with simple questions about what the shopper needs, who it is for, their budget, preferences and how they will use the item. Based on the answers and your catalogue data, it shows a short list of suitable products with photos, prices and a link to buy. Shoppers get help finding the right item, and you get higher-quality engagement than a plain search box provides.

ViV Softech Solution is a website designing and digital marketing agency in Delhi, and we build product recommendation chatbots as part of our AI chatbots services. It focuses on guided product selection for shops. For pre-sales Q&A on services and considered purchases, see sales enquiry assistant; for after-sales help, see customer support chatbot.

What It Helps Shoppers Do

Find the Right Item

Narrow choices by need, budget and preference.

Gift Suggestions

Ideas by occasion, recipient and price range.

Size and Fit Help

Guide shoppers to suitable sizes and variants.

Bundles and Add-Ons

Suggest items that go well together.

Product Comparison

Side-by-side differences in plain language.

Handover to Staff

Pass difficult questions to a person.

Rules First, AI Second

Not every recommendation chatbot needs advanced AI. For many stores, a guided flow based on clear rules works well: the shopper answers a few questions, and products tagged with matching attributes are shown. It is predictable, fast and easy to maintain.

Where shoppers like to type naturally, such as “something for a small balcony under 5,000”, AI can interpret the request and match it to your catalogue. We combine both: guided buttons for common paths and AI for free-text questions, always limited to products you actually stock.

How We Plan and Build Your Recommendation Chatbot

Quality recommendations depend on quality catalogue data. We begin by reviewing how your products are described and organised: categories, attributes such as size, colour, material, skin type or compatibility, price, stock status and images. If attributes are inconsistent or missing, we help standardise them, because a chatbot can only match what the data says. This work often improves search and filters on your store too; see product uploads and catalogue management and product image and description optimization. Next, we identify the decisions shoppers struggle with. This comes from your sales staff, customer messages, returns reasons and search terms. A fashion store might focus on occasion, size and budget, while an electronics store might focus on usage, performance and brand. We design a short question flow of three to five steps, with an option to skip, so recommendations arrive quickly. We define matching rules and ranking, for instance preferring in-stock, well-reviewed or higher-margin items, while keeping suggestions honest and relevant. Each result shows an image, name, price, key features and buttons to view or add to cart. We build the chatbot on your platform, whether WooCommerce, Shopify, a custom store or WhatsApp, and connect it to your live catalogue so prices and stock stay current. Sales conversations on WhatsApp are covered under WhatsApp chatbots and automation. We test with many scenarios, including shoppers who change their mind, ask for something you do not sell, give budgets too low for any product or describe needs in Hinglish. In each case the chatbot must respond helpfully rather than showing irrelevant results. Analytics track how many shoppers start the flow, complete it, click a recommendation and buy, using UTM or event tracking so you can see the effect. We review the data after launch and refine questions and rules. Customer privacy is respected: we collect only what is needed for the recommendation and disclose that the assistant is automated. We cannot guarantee sales uplift, as it depends on your catalogue, pricing and traffic, but a good guided experience can make choosing easier.

Typical Use Cases

Fashion and accessories

Occasion, style, size and budget.

Beauty and personal care

Skin or hair type and concerns.

Electronics and appliances

Use, features and compatibility.

Home and furniture

Room size, style and materials.

Food and gifting

Occasion, dietary needs and quantity.

B2B catalogues

Specifications and order size.

Health-related products need extra care; we avoid making medical claims and keep advice general.

Connected Growth Work

Recommendation data can feed marketing, such as follow-up emails with suggested products; see abandoned cart email workflows and ecommerce marketing.

For improving checkout after the recommendation, see landing pages and CRO and shopping cart and checkout setup.

What You Receive

Question Flow

Approved questions and matching rules.

Live Chatbot

Connected to your store and tested.

Performance Tracking

Starts, completions, clicks and orders.

Catalogue data clean-up is quoted separately if extensive.

Our Process

We check product data and attributes.

We identify the choices shoppers struggle with.

We design questions and matching rules.

We build and connect to your store.

We test varied shopper scenarios.

We track results and refine.

What Affects Cost

  • Catalogue size and data quality.
  • Number of product categories and flows.
  • Platform and live data connection.
  • AI free-text understanding.
  • Channels such as site and WhatsApp.

Frequently Asked Questions

Yes, both, plus custom stores.

Not always; guided rules often work well.

No, it uses live stock data.

Yes, with the WhatsApp Business API.

Usually three to five questions.

It may help, but results are not guaranteed.

Help Shoppers Find the Right Product

Tell us about your store and catalogue. We will plan a product recommendation chatbot and share a clear quote.

Call NowWhatsApp