Here’s the updated version of the Market Intelligence help content with the new Same product / Similar products keyword approach built in.

Sprintr’s Market Intelligence analysis is designed to answer one core question:

“Given how people look for this type of product over time, when should you lean in, when should you be cautious, and when is it smarter to ease back or reset?”
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This is not about forecasting sales or chasing trends.

It’s about timing awareness — understanding when market conditions are more likely to support action, when expectations should be managed, and when it may be better to ease back.

Sprintr combines market search behaviour with your own product context to build a clear picture of market timing.

Before analysing market trends, Sprintr first decides what kind of market signal is most relevant for the product.
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Not every product should be analysed using the same type of keyword.
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Some products are best understood by looking for the exact same product. Others are better understood by looking at the broader similar product category.
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Sprintr uses the product’s comparison type to decide this.

For products where the exact item matters, Sprintr keeps the strongest identifying terms.
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This is best suited to products such as:

For example:

Canon EOS 500D mk3, 28-55mm Lens Kit
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Sprintr may use a search term closer to:

Canon EOS 500D mk3 28-55mm lens kit
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This helps Market Intelligence understand timing patterns for that specific product or product family.

For own-brand, private-label, or category-led products, Sprintr may use a broader comparable-product keyword instead.
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This is best suited to products such as:

For example:

SCRUBD Anti-Ageing Face Moisturiser 100ml
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Sprintr may use a search term closer to:

Anti-Ageing Face Moisturiser

or:

Anti-Ageing Face Moisturiser 100ml
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This helps Market Intelligence understand the timing pattern for the type of product, rather than only looking for the merchant’s own brand.

Sprintr uses the same comparison logic as competitor analysis.

It applies this in the following order:

Auto-detection generally favours:

This helps Sprintr avoid analysing the wrong market signal.

For example, a branded camera and an own-brand moisturiser should not be treated in the same way.

Once Sprintr has selected the most relevant search term, it analyses long-range Google Trends data for that term.
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It looks for:

This data is treated as relative timing, not absolute demand.
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Sprintr is not asking:

“How big is this market?”
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It is asking:

“When does timing appear to matter most?”

Sprintr then layers in your real product performance to understand commercial relevance.
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This helps ensure the insight is grounded in reality.

For example:

Revenue is used for context only — not to predict outcomes or make promises.

Based on the trend shape over time, Sprintr classifies the product into one of four timing patterns.
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You’ll see the classification shown as a simple label, but the value is in the explanation and advice that follows.

ER

Products that appear relevant year-round, but see predictable lifts around gifting, retail, or seasonal shopping moments.
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This may apply to products that sell steadily but become more timely around periods such as Christmas, Mother’s Day, Father’s Day, Black Friday, or other retail peaks.

S

Products where interest concentrates into a clear part of the year, with extended quieter periods outside it.
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These products may benefit from being prepared ahead of the active period, while avoiding overreaction during naturally quieter months.

E

Products with broadly steady interest across the year, where timing appears to play a smaller role.
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For these products, pricing, content quality, margin, and product positioning may matter more than seasonal timing.

V

Products where the pattern is noisy, inconsistent, too sparse, or not strong enough to interpret confidently.
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Sprintr is deliberately conservative here.

If the pattern is not clear, it will not force a confident seasonal interpretation.

Sprintr turns the pattern into one clear market-timing insight, not a detailed report.

That insight:

If the most recent Google Trends data point is incomplete, Sprintr treats recent movement as directional only.

The keyword approach matters because a poor search term can create a misleading market signal.
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For example, using a full product title may be too narrow
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A title like:

SCRUBD Charcoal And Blackpepper Soap 250g

may not be the best term for understanding broader market timing.
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A better Similar products keyword may be:

Charcoal soap

or:

Charcoal and black pepper soap

depending on the product context.
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Likewise, for a model-led product, removing too much detail could make the trend too broad.
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A camera model, tool part, book title, or technical product may need its brand, model, or specification preserved.
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Sprintr’s aim is to choose a keyword that reflects the way people are likely to search for the relevant market — not simply repeat the full product title.

This is judgement-led guidance, not forecasting or campaign planning.

The recommendations that follow the insight are intentionally light-touch.

They are designed to help you:

They are not instructions to implement complex systems or controls.

They are practical guidance to help you make better timing decisions.

Market Intelligence may update when:

If the comparison type changes from Same product to Similar products, or the other way around, Sprintr may use a different keyword for trend analysis.

That can change the market pattern shown, because Sprintr is now looking at a different type of search behaviour.

When you see a Market Intelligence insight from Sprintr, you can be confident that:

Sprintr’s aim here is simple:

Help you move in step with the market — and avoid pushing too hard when timing isn’t on your side.