Monthly Archives: May 2013

Can Mobile Enhance Supermarket Store Revenues?

A March 2013 study tracked supermarket shoppers using Radio Frequency Identification to determine if shopping paths affected the amount of money people spent in a store.  The researchers found that the longer an individual shopper spent in the store the more money he or she spent.  In fact, increasing path length by 10% or 140 feet led to increased spending of $2.54 per shopper, a gain of over 16%.  Of course, marketers have always tried to keep shoppers in the store longer to increase sales.  That is why supermarkets place milk in the back and Ikea sets customers on an endless path.

This study is unique in that it added coupons to the mix to extend the shopping path. The researchers gave subjects coupons for items that were either near or far from their expected path.  When consumers received coupons for their unplanned items that led them on the far path they spent more money overall as compared to those who were given coupons leading to a shorter path through the store.

The implication for supermarkets is that management can use mobile couponing or shopping cart coupons to direct consumers on farther trips through the store to increase spending levels.  Mobile can also be harnessed to examine shopping lists to determine which items would be best suited for couponing. Specifically, when customers are in-store to purchase specific items, they may be more likely to respond to a coupon for that item.   The strategy doesn’t cost a lot of money.  Subjects in the far coupon conditions spent almost twice as much with only a $1.00 coupon.

Source:

The Effect of In-Store Travel Distance on Unplanned Spending:

Applications to Mobile Promotion Strategies

by

Sam K. Hui, J. Jeffrey Inman, Yanliu Huang, & Jacob Suher

Journal of Marketing Research, March 2013

A Critical Look at iProspect’s Adidas Mobile Case Study

Adidas, with the help of the digital agency iProspect, made a serious attempt to determine ROI on their mobile strategy. The process involved determining the conversion rate for those who clicked on the store locator page, the likelihood of purchase and the average purchase price. Here were the assumptions:

20% of those who click on the store locator page go to an Adidas store.
13% of all shoppers who walk into an Adidas store make a purchase.
The average store purchase is $71.

So far I have no problem with the analysis or the assumptions, though I have no way of independently evaluating them. iProspect’s next set of assumptions begin to lose credibility because they seem to embellish the numbers when they don’t say what they would like to hear – that mobile delivers a positive return on investment.

My first criticism comes when iProspect then assumed that the average purchase price for customers who click through the store locator page was higher than the average customer, now at $80 and that these customers converted at a 20% rate. Despite the embellishments the agency still found a negative ROI on a $1million investment in mobile.

Using the new assumptions iProspect then took the 494k clicks on the store locator page over a certain period of time and did the following calculation:

494k clicks on store locator page x .20 store visits x .20 purchase @80 = $1,580,800

The analysis then reasonably added the $230k in sales generated from direct mobile clicks plus the additional sales based on those who clicked on the store locator page for a total revenue of: $1.81 million.

The problem with the analysis is that it assumes that everyone who goes to the Adidas store locator page is a new prospect who was not planning to go to Adidas that day or on another day to make a purchase. Those who click on the store locator page may already be Adidas customers who would spend $80 on a purchase anyway. Therefore, to attribute the full value of the conversion to the store locator page only accounts for the last click. The result is a limited view of the purchase funnel in an attempt to boost mobile value.

That said I do not denigrate the value of mobile, just that marketers should be clear on what the numbers really mean. When agencies embellish the value of their efforts masked by metrics, they lose credibility.

Source: The Full Value of Mobile Case Study: adidas and iProspect explore an innovative approach for measuring mobile’s impact on in-store conversions, 2012 Google.

Oreo Boys

Oreo Boys

Two men wearing Oreo shirts on my corner waiting to populate Union Square?
This campaign led me to consider the reach of the campaign and the impact on the brand. This photo was taken at 10 AM, May 14th, 2013. At 8:30 PM I ran Social Mention for both Oreo and Wonderfilled, the new tagline. Wonderfilled had a 44% Reach (number of unique posters), but Oreo had 50%, most likely due to media postings. The reason I suggest that media is responsible is because Wonderfilled’s sentiment was 17:1 compared to Oreo’s 11:1.  Sentiment is a ratio of positive to negative mentions.  Oreo’s are more neutral, suggesting articles written by professionals.

Social mention is a tool that can be used to compare brands and their social media positions. It’s not perfect, but nice for a quick snapshot.

Emotional States of Internet Users: East vs. West

A study in the European Journal of Marketing categorized segments of consumers based on their emotional states of being. Some people experience more emotion in the real world, while others are equally emotional online as offline.  The study identified 6 groups of internet users:

  • Positive online affectivists feel anxiety and stress in offline situations in the real world, but exhibit happiness, confidence and imagination online.
  • Offline affectivists experience the most emotionally intense feelings offline in the real world.  Online they feel anonymous. 
  • On/Offline negative affectivists feel anxious and stressed both online and offline and experience higher levels of negative emotions in general. They feel anonymous online.
  • Online affectivists have intense emotional experiences online and are happiest operating on the internet.
  • Indistinguishable affectivists have neutral feelings about both the online and offline worlds.
  • Negative offline affectivists:  Feel anxious and stressed offline, but brave and powerful online.

The study is interesting in that some people are more comfortable in their online selves than in the real world and prefer to interact with others mediated by the internet.  They may be better targets for social media marketing efforts.

The study also examined people around the world and the clusters in which they fell.  Specifically, North Americans were more likely to be offline affectivists, while the Chinese respondents were more often positive online affectivists.  East Asians were heavily represented in the online affectivist category.  Offline affectivists and negative offline affectivists were found to be more female. 

An important finding for marketers is that those who experience positive online emotions are more likely to support brands’ online activities. 

 

Source:
Title: A typology of internet users based on comparative affective states: evidence from eight countries
by  Christodoulides, George; Michaelidou, Nina; Nikoletta Theofania Siamagka

European Journal of Marketing, 47, 2013

Real Time Bidding at the Mobile Marketing Forum

Programmatic buying also known as Real Time Bidding (RTB) was a topic at today’s Mobile Marketing Forum in New York.  Publishers online have been allowing their inventory to be sold through programmatic buying programs, but mobile is poised for growth in this area.  Right now there is a lot of inventory in mobile advertising that could be sold to advertisers who execute a strong strategy.  The key for publishers is to package their offerings by clearly indicating the value added to advertisers,  identifying the targets and the deliverables.  One clear selling point for mobile ad inventory is the location based data that can be mined for advertisers. 

Publishers may be worried about selling their premium content in an auction system, but the publishers who use these services can retain their premium clients and sell RTB to other advertisers who would not normally purchase premium content.   For example, the Wall Street Journal has premium advertisers, but sells to Virgin Atlantic Airways via RTB, the only method this company uses to buy advertising from the WSJ. 

The advantage in RTB for publishers is to sell more inventory at higher prices while advertisers buy the targets they really want.  It’s a win/win according to Rubicon. 

The market is shifting with 15-20% of online ads purchased programmatically online and soon in mobile.  Marketers can still get strong CPM’s, but the RTB system will lead to higher rates going forward.   

Source: Mobile Marketing Association Forum, May 9th, 2013: Maximize Mobile Advertising Revenue – Can Programmatic Help? with Joe Prusz, Ingrid Lestiyo and Josh Wexler

Live from the Mobile Marketing Forum

This post is live from the Mobile Marketing Association Forum in New York. The session titled: 360 degree view of mobile along the path to purchase moderated by Matt Weiss from ePrize had some good examples of how mobile can drive customer actions.

For example, Bank of Montreal developed a mobile app to help customers in the home buying process with the ultimate goal of either getting customers into the branch or selling mortgages.

One of the most effective ways BMO drives customers into branches is with their ice cream truck that is integrated with their mobile strategy. The Bank of Montreal mascot BMO Bear accompanies the truck and kids and parents take pictures with the bear and post them online. To get a print out customers must go into the local branch. The activity is engaging and not directly selling bank services. According to Pritesh Gandhi, Senior Manager Digital Strategy for BofM, it’s about the experience, but the bank must justify the expense with results.

Unilever is trying to engage customers in the buying journey by offering value added services that are not brand specific. For examples, it is 4 pm and mom is at the office. What does she need to pull together to make dinner happen? Smart kitchen, a mobile app that is integrated with a loyalty program at the retail level, can tell mom if she is running low on items in the pantry.

The big take away for this session was that marketers should not attempt to change consumers’ natural behaviors, but instead figure them out and add value to people’s experiences.

Social Networker Antecedents and Behavioral Outcomes

Individual’s willingness to participate in social networks as well as their likelihood to continue to use them, recommend them and join other social networks is based in a certain set of beliefs including (Lennon, Rentfro, & Curran, 2012):

* Ease of use – Does using social networks require effort on the part of the user?

* Usefulness – Do social networks improve the way users complete networking tasks?

* Enjoyment – Are social networks fun, pleasurable, or entertaining?

* Social influence – Does social influence contribute to the use of social networks?

* Drama – Do emotional interactions on social networks affect users?

Source: 

“Exploring relationships between demographic variables and social networking use”

by Ron Lennon, Randall W. Rentfro, Randal and James M. Curran

in Journal of Management & Marketing Research, September 2012, Vol. 11, p1