Why seasonality matters

Seasonality in customer reviews can make a store look like it is getting worse when it is simply busier. In Indian retail, festive periods, wedding seasons and big sales change who shops, how many, and what goes wrong. Reading a festive month against a quiet one misleads.

Typical patterns

  • Festive peaks: more reviews; more mentions of crowding, waiting, billing and stock.
  • Wedding season: more custom orders, alterations and delivery-date mentions, especially in jewellery and ethnic wear.
  • Sales: more price and offer mentions, more returns and exchanges afterwards.
  • Quiet months: fewer reviews; staff attention and product topics dominate.

Comparing fairly

  • Compare each season with the same season last year.
  • Align by festival dates where they move year to year.
  • Look at topic shares, not just counts.
  • Note store openings and closures that change the mix.

Planning for peaks

  • Review last year's peak-season reviews by store before the season.
  • Add billing and floor staff where waiting complaints peaked.
  • Set realistic delivery dates for custom orders.
  • Check stock for the products customers asked for and could not find.

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An example

A jewellery chain's billing complaints jump every Diwali week. Comparing year on year, the jump was smaller this year at stores that added a temporary billing counter, and larger at stores that did not. Next year, every high-volume store gets the counter.

After the season

Run a short post-season review: what customers praised and complained about at each store, compared with last year, and three changes for next season.

Trends

Sentiment trend analysis: reading month-on-month change.

Sentiment trends reading month on month change

Common mistakes

  • Comparing festive months with quiet ones.
  • Ignoring moving festival dates.
  • Planning peaks from memory instead of reviews.
  • No post-season review.

Common questions

Do reviews lag the season?

Some arrive days or weeks later; allow for that in the window.

Does seasonality affect ratings?

Peaks can bring more complaints and more reviews; look at topics to see why.

How many seasons of data do we need?

One year gives a first comparison; two years shows whether patterns repeat.

What about weather?

Monsoon and heat affect footfall and some topics, such as parking and comfort.

Checklist

  • Year-on-year comparisons.
  • Festival dates aligned.
  • Peak plans from last year's reviews.
  • Post-season review.

In short

Seasons change review volume and topics. Compare each season with the same one last year, plan peaks from last year's reviews, and review what happened after each season.

Build a season calendar

List the periods that matter for your business, such as Diwali, Akshaya Tritiya, wedding seasons, end-of-season sales and school holidays, with their dates for each year. Tag reviews by season. Year-on-year comparisons then line up automatically, even when festival dates move.

Staffing from last year's reviews

The most practical use of seasonal review data is staffing. Look at which stores had the most waiting and crowding complaints during last year's peaks, and at which hours, and plan temporary staff or counters for exactly those stores and times.

Doing this with Falcon

Falcon shows negative share by topic, location and month on one heatmap, flags locations with too few reviews to compare, and lets you compare any period with the one before or the same weeks last year, so a location's problem can be told apart from a network-wide one. Every number opens the reviews behind it, in customers' own words, so a comparison can always be checked.