Quantitative Research


Sam Elphinstone from the numbers lab talks about getting more from quantitative studies

Researching retail is fascinating.  Whilst always a dynamic and exciting category it has recently become even more so, as brands seek to seamlessly join their digital and non-digital offers.  The ultimate aim is to present customers with a slick and enjoyable experience, minimising the opportunities for customers to disengage and maximising share of wallet.
Whilst preventing people from leaving the purchase funnel is of huge importance, there are some other considerations identified from research carried out specifically around fashion retail that can play a significant role in whether or not a sale is achieved.

Chief amongst these considerations is increasing the likelihood that shoppers will plan a visit. Across both digital and physical stores, if a visit is planned, a sale is 2½x more likely.  Furthermore, planned visitors are 2 times as likely to visit again in future.  Interestingly, this is irrespective of how close the shopper is to the brand initially.

Planned visits tend to be in the minority (around 20% of shoppers), with the majority of decisions around visiting a particular store or site made on an ad hoc basis, whilst browsing online or wandering through the mall.  Obviously, converting these ‘floating’ shoppers with a clever media strategy that interrupts them at the most opportune time is essential, especially as there is probably a limit to the number of planned visits that can be achieved.  However, given the role they play in maximising the aforementioned share of wallet, growing the 20% of planned visits is a proven way of achieving growth.

So how can we drive shopper planning?  Some of it comes down to old-fashioned top of mind awareness and saliency in what can be (especially in the world of fashion retail) a very crowded landscape.  How we drive those metrics should come as no surprise; traditional ATL and BTL communications designed to hit a broad audience allied with more tailored digital and social media campaigns with a more emotional connection in mind.  CRM can also play a crucial part, tailoring the engagement and rewarding loyalty.

What may come as a surprise is the extent to which the ‘basics’ mentioned above aren’t done correctly or often enough, meaning that awareness is subject to peaks and troughs which, in turn, affect the extent to which visits are planned.  In recent conversations with clients, we are also seeing marketing spend diverted from those ‘basics’ into other areas, such as the blending of digital and non-digital customer experience mentioned earlier in this article.  

The former issue can be addressed by taking a slightly more radical view of brand impact marketing, perhaps by adopting an ‘always on’ strategy which substitutes big, infrequent and expensive campaigns with a cheaper more agile alternative that maintains a more consistent presence.

The latter is about understanding priorities.  Getting the customer experience right across all of your properties is essential, however, it should not come at the cost of driving planned visits impacted by more traditional metrics like awareness and saliency.  For the health and wellbeing of retail there needs to be room for both.

Sam Elphinstone is Group Head at the numbers lab. His expertise focuses on understanding how brands interact with consumers. He is a specialist in consumer experiences, how people react to them and their subsequent impacts on behaviour.


Anne-Marie McCallion from the numbers lab talks about getting more from quantitative studies

Clients constantly challenge their agencies to go further, to provide insights which really and truly deliver on what’s on the minds of their customers. As one recent client brief so eloquently put it, “we don’t want you to spend time regurgitating our objectives back at us, and talking about sample structure, but want you to provide a methodology that is going to capture attention”.  While those old tried and tested methodologies still form the core of what agencies do to get to the answer, new and exciting technologies that can enhance these are becoming more prevalent. 

The best of these new approaches have a common theme – the ability to collect “in-the-moment” feedback. In essence this is pure and simple but, when correctly executed, it allows us to deliver deeper, real world insights to our clients, with recommendations that steer them forward.

Some of our most considered digital research technologies include:

1.     Adding a video element to our studies: Building a video element into online surveys elevates the typical open-text verbatim comments and increases engagement for respondents, improving the quality of feedback. Bringing the faces of consumers into the room at a client debrief brings the findings to life, and increases engagement for stakeholders. This technology can be integrated into everyday tracking studies to gain rich brand insight or into ad testing pieces to collect live and in-the-moment responses.

2.     Using facial expressions to accurately predict success: One step further than using videos within surveys, facial coding allows us to read the emotions of survey respondents in the moment. While typical survey diagnostics allow us to collect feedback post-viewing, facial coding goes deeper, to pinpoint the initial emotional connection respondents have to a piece of stimulus. This, in turn, also allows us to understand the reactions respondents will not or cannot vocalise.

3.     Collecting passive data: There are often times when we expect too much from our respondents. In times of increasing market and advertising clutter, spontaneous and prompted recollection is difficult. Discreetly collecting passive data (with permission, of course) from our respondents’ laptops and devices gives us the ability to measure actual behaviour and deliver more robust insight to our clients.

The potential benefits are clear, but such technology should be approached with care. Using additional methodologies for the sake of it doesn’t help anyone and only serves to mismanage expectations (and budget) in the mind of your clients. The challenge here lies in the careful curation of a methodology that uses the best of the traditional methods, alongside carefully selected, complementary methodologies to move beyond the stated and more towards actual customer feedback. 

Couple this approach with statistical analysis tools like Conjoint, MaxDiff or Kano analysis, it means that we can place the onus on our analysis of the data, lightening the cognitive load on survey respondents. By doing this, you are allowing them to think about answering honestly, and to not have to indulge in complex thinking to get to an answer they think is right.
After all, isn’t that we are client partners in the first place?

Anne-Marie McCallion is Associate Director at the numbers lab. She loves a challenge and believes that research is not a one-size-fits all exercise. She is an expert at reading between the lines and has a keen eye for detail.