Online and Offline Retailing

An article in The New York Times titled “Unboxed, A Data Explosion Remakes Retail” by Steve Lohr caught my eye with a fantastic example of a retailer using a cleaver online idea to drive sales instore.

http://www.nytimes.com/2010/01/03/business/03unboxed.html?em

The retailer is US company called Wet Seal, they have 500+ stores and sell fast fashion mostly to female teens.

They have created a web feature called “My Boutique” where users can create outfits from their stock keep them in their own online closet and also post them online. Other users can then search through the posted outfits, review them, post comments and view top rated outfits. They have so far had over 300,000 posted outfits.

They have also broadened the offer to an iPhone application called iRunway that can be used instore to search user-generated outfits from specific garments instore.

For my mind this one of the best examples of a retailer linking online and offline retail in a strategy that not only drives sales through both channels, but improves the shopper experience and provides a gold mine of customer intelligence through user-generated content.

10 reasons to care about the shopper

 

I read a piece in retailwire titled: Ten reasons you should care about the shopper by Joel Rubinson http://www.retailwire.com/Discussions/Sngl_Discussion.cfm/13892

The article looks at the why shopper insights are important to today’s marketer or retailer.

Notable points for my mind:

• Fifty percent or more of product and brand decisions are made in-store.
• The mind set of a shopper is different, it action and decision focused. In-store promotion needs to take this into account.
• Shopper insights and consumer insights are different things. Consumer insights study preferences; shopper insights study how people put preferences into action.

Traffic measurement for multichannel retailing

An article published by Experian FootFall and Hitwise outlining best practice for measuring traffic on and off line.

http://www.etailtoday.com.au/Articles/tabid/54/Latest/128/Measurement-for-multichannels.aspx

New report identifies the UK’s post-recession ‘bounce-back consumer’

The latest Experian Insight Report shows that the post recession consumer has drastically different spending behaviour.

▪ Over 40% of consumers believe companies are not fair to customers

▪ More than 80% of consumers are ‘increasingly aware’ of prices, but that doesn’t mean going downmarket

▪ Keen pricing, rewarding loyalty and customer service – not just lip service – will be key to winning the fight for the bounce-back consumer post-recession

For the full article http://experian.global-pressoffice.com/documents/showdoc.cfm?doc=3519

On-line vs In-store

I read an article in retailwire titled “Its time for retailers to transform their stores”

http://www.retailwire.com/Discussions/Sngl_Discussion.cfm/13606#poll 

The author Natt Fry looks into why on-line sales are outpacing in-store sales from a growth and customer satisfaction perspective.

Her big four reasons for this trend were:

1) Rapid product and price comparisons available on-line

2) Growing public comfort with on-line security and overall convenience

3) Increased access to the internet

4) Superior analytics and consumer insights that can be derived from e-commerce allow for more targeted offerings

 

These are clearly the strengths of e-commerce – the question is what can traditional bricks and mortar retailer do to level the trend?

The answer must be differentiation. In-store retail has something the web can never offer which is the ability for the consumer to interact with your products and the opportunity for sales people offer value to the client at the point of purchase.

Emotion-recognition software

Dutch researchers from the ISLA Laboratory at the University of Amsterdam have developed a software application that can read human emotion.

The application detects the movement of thousands of tiny facial muscles working when we smile, frown of grimace. The Emotion-recognition software, or ERS, creates a 3-D face map, pinpointing 12 key trigger areas like eye and mouth corners.

A face-tracking algorithm matches the movements to six basic expression patterns, corresponding to anger, sadness, fear, surprise, disgust and happiness, or a mixture of them.

The university has created a company – Visual Recognition http://www.visual-recognition.nl/ to take the application to market. To date they have worked with Unilever to test responses of 300 European women to differing foods.

Unilever’s interest in the technology lies in market research where the technology may be used to test people response to low fat or calorie reduced foods.

The software represents an exciting opportunity for gathering of raw consumer response data. 

The algorithm can be tested at http://www.gladorsad.com/en/

Social Technographic Profiles

Do you know how your target audience uses blogs, social networks (Facebook, MySpace, Twitter ect), and YouTube?

Forrester Research have profiled and grouped the differing ways people use social computing sites into what they are calling Forrester’s Social Technographics®. They have identified six overlapping levels of participation – Creators, Critics, Collectors, Joiners, Spectators and Inactives.

 

 

Understanding how your target audience interacts with social computing sites will go a long way when developming a social computing strategy.

You can get a feel for the profiling at http://www.forrester.com/Groundswell/profile_tool.html where they have classified 11 countries by age and sex for their relative Social Technographic® profile.

Social Mapping with Socialight

Socialight (http://socialight.com/) has created a google maps mash-up that allows users to tag geographic locations with content (text, photo or music) to be shared with their friends.

When members of the same social network come in close proximity to the location the content is then sent to their mobile. Socialight has its own member groups and has links into Facebook and Myspace.

This could be a great way for retailers to increase instore traffic by communicating with their members who are close by.

Socialight has a video on youtube that is great introduction to their service http://au.youtube.com/watch?v=9KeFXtRJLG8&eurl=http://socialight.com/

RFID and In-store Customer Insight

There is an exhaustive amount of material published about RFID technology assisting with logistics, supply chain and inventory management but little on its other potential applications.

Paxar and The Big Space in 2007 collaborated on the magicmirror http://magicmirror.thebigspace.com/

The magicmirror uses RFID technology to present product specific content to shoppers whilst they are standing at the mirror.

Asides from customer service and sales benefits the most relevant information comes from analytics in the background. One example is understanding interest vs. purchase – this kind of data can be valuable in helping retailers to optimise product mix and offering.

I am sure this is the tip of the iceberg for RFID and customer insight so it will be interesting to see what the future holds as the cost of RFID continues to decrease.

Fujitsu lunches Customer Experience Diagnostic for Retail

Fujitsu Services has launched a new service that will help retailers measure the in-store customer experience.

http://www.fujitsu.com/uk/news/pr/fs_20090127.html

It looks like the offering uses multiple techniques to measure service delivery, such as transaction speed, queuing times, store layouts, mystery shopper audits and customer service benchmarks.

Once service delivery is measured they identify weaknesses, offer solutions to address the weaknesses and  then test the recommendations in a controlled environment.

Whilst very appealing on the surface I would be interested in the cost of solution and how they help retailers to maintain the changes they implement.

Key Attitudinal Indicators (KAIs) by Confirmit

 

In the current economic climate loyalty and customer experience are being identified as key focus points for retailers looking to stay ahead of the game.

However this begs the question – how do you measure loyalty and customer experience?

Confirmit’s answer to this question is their feedback management software that uses event-driven online feedback surveys at key moments in the customer life cycle to measure customer attitude.

This traking of customer attiude can lead to the formulation of key attitudinal indicators (KAIs) which can provide organisations with a predictive measure of likely future performance.

 http://www.confirmit.com/solutions/industry/retail.aspx

What does your store smell like?

ScentAir http://www.scentair.com/  is an innovative company unlocking the power of the olfactory sense to do everything from increase sales, boost productivity and improve brand recall.

They have numerous studies showing 50% increases in slot machine takings from rooms with ScentAir to 80% increases in surveyed respondents willingness to purchase shoes.

Bloomingdales use ScentAir to provide the scent of baby powder in the infant department appealing to a mothers memory and coconut in the swimwear department to create a beachy feel.

Lexus use a mix of green tea, lemongrass and vanilla grape fruit to add to the show room experience.

The only question left is what smell is your store missing?

Realising the Potential of Retail Analytics

 I was directed to a great piece of research by Tom Davenport and the Babson Working Knowledge Research Center on the Marketing Metrics blog:

 

http://metricsmarketing.blogspot.com/2009/02/professor-tom-davenport-advises.html

 

The research explores 18 current trends and 5 future trends in retail analytics. It also looks into some of the challenges to implement analytics in retail and provides suggestions on how to avoid these.

 One of the current trends that are of particular interest is “Store Level Empowerment”. Davenport suggests that whilst many retailers are centralising their analytic function some retailers are increasing store level capabilities with good results.

 Examples include “Electronics retailer Best Buy (that) provided district, territory, and store teams with tools to analyze store traffic levels, activity by zip code, sales close rates, customer satisfaction, segment activity, and market share by segment. Store managers were also given simulation tools to analyze how different variables contribute to store revenue and profitability. With the use of these tools, Best Buy was able to move to more granular predictions of chain-wide revenue and profit growth, which proved more accurate than centralized forecasts.”

 The full report can be found at http://www.sas.com/events/cm/622624/index.html