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How shopper behaviour intelligence differs from other data sources...

Please note that this a real case study - we've just changed the names.

The facts

Unlike many case studies, this one doesn't have a happy ending, but it's one that we felt compelled to share because of its rich learning content. Quite a few years ago, we identified a fairly big shopper brand loyalty risk to a 'leading nappies brand'. Sadly the client whose brand it was couldn't quite believe what we were telling them. In 2006, this brand had 80%+* share of the Australian market. Today it has 63%*. This loss impact could have been reduced.

* Source: Retail World Annual Report.

The challenge

At the time, shopper insights were the new kid on the block compared to consumer. Consequently understanding of what shopper insights actually meant and what to do with them was in its infancy. The client was struggling to come to terms with the risk % we presented. We were also a new agency to them & with hindsight, could probably have done more to handle their education in critical metrics such as shopper brand loyalty risk. Combined this meant that our client was quite literally in shock when we presented bad news to them that there was a potential 17-20% risk to this brand's market share.

Their disbelief stemmed from the fact that every other piece of research they had ever seen had painted this brand in a glowing light and it passed all brand health tests with flying colours. The problem was due to the apparently logical assumptions made about the various data they had. For example, market share data was 80%+ so that's good right? In addition, panel data was saying that it was the same loyal households that were buying this brand week after week; so another tick. Brand health trackers were showing that when asked about this brand, consumers gushed & couldn't have higher praise for how amazing it was compared to the others; yet another tick!

So why was our information throwing a spanner in the works?

The solution

The reason was - and is - how loyal a shoppers' behaviour is and this was totally new insight to the client. Imagine the shopper scene... a busy Mum is at the nappies shelf and she can either:

  1. walk up to the brand, spend very little time selecting it (because she knows what she wants), hardly glance in the direction of other brands and put the same (& planned) brand into her trolley.
  2. walk up to the fixture, spend some / quite a lot of time selecting (because whilst she always buy this leading brand she is thinking of changing for X & Y reasons), but after lengthy deliberation and much product handling, she walks away with the usual (leading) brand in her trolley.

Both of these shoppers feature in the 80%+ market share number, are loyal according to panel data because they buy this brand week after week and in brand health trackers still talk about how good the brand is.

Yet, their behaviour at the shelf shows one shopper who is loyal (habitual or genuinely loyal is another story...) and the other shopper whose behaviour is actively considering change. This is what we call behavioural shopper loyalty and is just one of the behavioural factors that goes into our overall shopper brand loyalty risk metric.

The results

The leading brand still enjoys 63%+ market share, so it's not all bad, but when a new brand entered the category in 2008 that was 'good enough' in performance at a much lower price, the leading brand's market share was hit. So what's the moral of this story? I guess three things:

  1. Be prepared to listen to bad news.
  2. Recognise how different data sources have different roles to play.
  3. Be adaptable in strategies & tactics to focus on the areas known to drive the most impact with shoppers and mitigate the known risks.

 

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