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Using Google Trends To Plan Ecommerce Merchandising

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I have worked with a number of ecommerce retailers before, two of them being well known brands, one in the UK, the other in the US. The interesting thing I learnt about buying and merchandising teams is that, especially in fashion, the buying is often done on “gut instinct” as well as checking out the latest trends, especially amongst celebrities and the catwalk.

On the other hand, merchandising is usually carried out based on margin expectations, stock levels, business promotions and disposal of old stock. A lot of these are based on physical world merchandising, and a lot of these methods spill over into ecommerce sites. However, conversion optimisation has started playing a role in online merchandising, but many businesses have a long way to go before they get it really spot on.

So where does an SEO come in?

Well, apart from trend data from the fashion mags and industry chatter, there aren’t very many sources of information on what people want to buy. Or is there?

I remember having a couple of arguments about product naming conventions for example. I would prefer to use (obviously!) SEO friendly naming conventions for a number of products, or variations thereof, on the other hand the teams in the B&M departments would prefer to use “brand” type names. And they aren’t wrong – launch a line of products that are really good, give them a really cool name, and they can take off. And in such cases I would often lose the argument, except for a few key essential wins.

On the other hand, these conversations got me thinking – WHY don’t we use publically available data to merchandise and market offline? I use a number of keyword tools, google trends, hitwise etc.

A Practical Example

Let’s say the business that we are looking to help sells womens clothing. One of the items is “Leggings”. What does Google tell us about them?

Over the last two years, the peak increase in search volume for “leggings” seems to start around the July mark. Might be obvious to someone that is in the fashion industry, but not to someone new to it, or to a business that doesn’t plan around peoples interests.

What would I do?

  • Personally launching ANY new lines of leggings would be advisable at the start of that search peak.
  • Making sure that a full range of leggings are available, indexed and found via search engines.
  • Making sure that these are easily seen across key areas of the site.
  • Make sure I have enough ranges to take me into and all the way to end of Jan.

What else does the data tell us?

Well to start with, it tells us the top keywords in the space, which could be further plotted to see which are seasonal trends and which are normal trends:

As you can see from the chart, “black leggings” (as is to be expected – a common colour) has a much higher average index, and should really be an “all year” product. It doesn’t take the same level of a dip in the year as the other two keywords do.

That gives me what stock to keep all year round…

The data also gives me breakout keywords –such as indicated by the charts below:

I have no IDEA what Galaxy or Aztec leggings are, but if the business even remotely stocks a pair that can be referred to as either, I would merchandise those with a bit of priority. The best time to keep an eye on these trends are as the search volume ramps up – and if your supply chain is fast, you can get the stock in quicker than your competitors, especially for the winter peaks, as often these fashions carry on for months.

Summary

There is a lot of open, free data available on the web. And as such, a clever ecommerce business should try and utilise such data to test making business plans. After all, it’s just a variation of consumer research isn’t it? I have only explored one way to use such data. However in my time in digital marketing, I have often used datasets like these to influence more than just digital decisions.

The data can be used in a number of ways:

  • Planning the buying cycle
  • Stock rotation policy
  • Ordering trending stock (trend watching)
  • Managing naming conventions (wet look vs shiny for example)
  • Planning offline marketing campaigns to coincide with growth of interest
  • Merchandising stores and websites by search volume indices
  • Estimating demand year on year

What else can you think of adding to the list?


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