When Google began showing AI-generated summaries at the top of many results pages, most site owners expected a shift in how searchers interact with content. What few predicted was how quickly those summaries would answer questions that once sent people to product pages, category pages, and buying guides. For Indian e-commerce sites, which often depend heavily on informational queries to bring in shoppers before they reach a purchase decision, the change has been felt sharply. Google AI Overviews are cutting clicks in many categories, and understanding why is the first step toward building a response that holds up.

What Google AI Overviews Actually Do

Google AI Overviews are AI-generated summaries that appear above the traditional list of organic results for certain queries. Instead of asking a searcher to open several pages and piece together an answer, the overview pulls together information and presents it in a short block, usually with links to the sources it draws from. Google has described the feature as a way to help people get to the gist of a topic faster, and it is available in India for a range of search queries. The rollout has been gradual, and not every query triggers an overview, so the impact varies by keyword type.

For e-commerce, the important detail is which queries trigger these summaries. Informational and comparative searches are the most affected. A query such as "difference between cold press and refined coconut oil" or "best way to store basmati rice" is likely to produce a summary that satisfies the searcher completely. A query like "buy cold press coconut oil 500ml" is far less likely to be answered by an overview, because the user is ready to transact and needs product listings, prices, and seller options. That split matters a great deal for how you should respond.

Why Indian E-commerce Sites Feel the Impact More Acutely

Many Indian e-commerce brands, from fashion labels in Delhi's Karol Bagh and Chandni Chowk wholesale ecosystem to health and grocery platforms serving tier-two cities, have built large content libraries around educational questions. Buying guides, ingredient explainers, size charts, sizing advice, and "how to choose" articles were designed to attract traffic at the top of the funnel. When an overview answers the top-of-funnel question on the results page itself, the visit that would have followed never happens.

Several factors make the effect more pronounced in this market. Mobile-first search behaviour means that screen space is limited, so a summary block occupies a larger share of what a user sees before scrolling. Price sensitivity and the habit of comparing options before buying also mean that shoppers often run multiple informational searches before committing. And in categories where product differentiation is subtle, such as spices, textiles, or electronic accessories, the overview may tell a searcher everything they need to know without any reason to visit a store.

None of this means that informational content has lost its value. It means that the way value is delivered has changed, and sites that depended on a single traffic pattern are exposed.

Measuring the Drop Without Guessing

Before changing strategy, it helps to confirm what is actually happening on your own site. Attributing every decline in organic sessions to AI Overviews is a common mistake. Seasonal demand, algorithm updates, competitor price moves, and technical issues can all cause similar patterns.

Start by segmenting your Google Search Console data. Look at queries that were previously driving traffic and check whether their impressions held steady while clicks fell. A pattern where impressions stay roughly level but click-through rate drops sharply on informational queries is consistent with an answer being shown above your listing. Compare this against commercial queries, where clicks may remain stable. Pay attention to query types: "what is," "how to," "best," "vs," and "benefits of" searches are the ones to examine first.

You can also run manual checks for your priority queries in an incognito window and note whether an overview appears, what sources it cites, and whether your domain is among them. This is slow, but it gives you a clearer picture than aggregate traffic numbers alone. Keep a simple log so you can revisit it over time, since the presence and format of overviews change.

Separating Informational Traffic from Buying Intent

The most useful step many e-commerce teams can take is to stop treating all organic traffic as equal. A visit from a "what is" query and a visit from a "buy" query may both count as a session in your analytics, but they represent very different opportunities.

Group your keywords into three rough categories: informational queries where users are learning, comparative queries where they are narrowing options, and transactional queries where they are ready to buy. Expect AI Overviews to affect the first category most, the second to a moderate degree, and the third least. Once you have this map, you can decide where to invest effort and where to accept lower traffic in exchange for stronger conversions.

There is a practical consequence here. Some informational pages may no longer be worth the same investment, especially if they were written to capture broad, low-intent traffic. Others may still justify their place because they support product discovery, build trust, or feed into internal links that move users toward category pages. The goal is not to delete content reflexively but to assess what each page actually contributes.

Practical Responses for E-commerce Teams

Strengthen Product and Category Pages for Commercial Queries

When shoppers search with purchase intent, they still need what overviews cannot provide in full: current prices, stock status, delivery options, return policies, and a checkout path. Make sure your category and product pages answer the questions a buyer asks at that stage. Clear specifications, honest comparisons between variants, customer reviews with substance, and transparent shipping information all help. Structured data for products, reviews, and availability can help search engines understand these pages, though it does not guarantee a particular display treatment.

Rework Informational Content Around Decisions, Not Definitions

A definition is easy for an overview to summarise. A decision framework is harder. Instead of writing "What is organic cotton," consider content that helps someone choose: which cotton grade suits their climate, how to read certification labels, what to look for when a price seems too low. Tie these guides to specific products and categories through contextual links. The reader gets genuinely useful guidance, and the page has a reason to exist even if the overview covers the basics.

Build Content That Overviews Are Likely to Cite and Users Want to Verify

Overviews include source links, and some users click through to confirm information or explore further. Pages with original data, clear authorship, specific measurements, or first-party product testing give people a reason to follow the link. Be careful here: do not invent testing results or statistics to appear authoritative. Only publish findings your team has actually generated. Where you cite external research, link to the original source.

Invest in Formats That Are Harder to Summarise

Interactive size finders, calculators, configurators, comparison tools, and video demonstrations are difficult to reduce to a text summary. A fabric care calculator that recommends wash settings based on inputs, or a tool that helps someone estimate how much paint they need for a room, offers something a search overview cannot replicate. Such features require development effort, so prioritise the ones that tie directly to your product range and purchase journey.

Strengthen Brand Demand and Direct Traffic

Search is only one channel. Email lists, WhatsApp communities, marketplace storefronts, returning custom