1. MOBILE MARKETING IN PRACTISE: MORE SOPHISTICATED SMS CAMPAIGNS & TARGET FILTERING Course Faculty: Mrs Yasmin Malik Venue: IBA City Campus, Karachi Course Start Date: Spring 2012 (Feb 1) MIS553: Mobile Marketing Strategies

2. Marketing: Traditional vs Mobile  In traditional marketing, tracking and targeting are considered crucial to the success of your campaign  Although these are sometimes discussed separately in traditional marketing  In mobile marketing: the two must be considered together  This is due to the very personal nature of the message and the increased ability to track your customers’ interaction via the mobile platform  In many cases, it is the Operator which is in a very good position to provide targeting/segmentation related information to brands  In mobile marketing:  Targeting = both identifying key demographics and adapting your marketing message to their needs  Tracking = any attempt to capture and evaluate data about the effectiveness of your mobile marketing campaign

3. Targeting: Age and Gender  According to a 2008 study by m:Metrics, the best demographics you can reach with mobile marketing is:  Men between 18 and 34 years  70% of iPhone users are Male (comScore 2009 study)  Hold on: Women are still important!!  A 2009 study called “Women and Digital Life” reported that females between 12 and 24 years of age named their mobile phones as the most important piece of technology in their life  Similarly, a 2009 Greystripe study showed that 43% of mothers are more likely to download mobile content and that 29% of iPhone owners are women with children  In Pakistan: all Operators concede that gender cannot be established with 100% reliability due to multiple SIM usage and registrations

4. Targeting: Income + ARPU  Income or “spending power” in many ways determines how much mobile subscribers are willing to spend on mobile based advertising or usage  Income can be associated with the Socio Economic Class (SEC) that a mobile subscriber belongs to: A, B, C etc. (where A is the highest income bracket and denotes “affluent” users)  Related to Income is ARPU which is a direct measure of the mobile subscriber’s spend on his mobile connection on a monthly basis  In general, mobile consumers in a high income bracket tend to rely more heavily on mobile content than those in the lower income scale (2009, comScore study)

5. Targeting: Age, Gender & Income (Demographics)  A 2008 iCrossing study showed that the largest portion of mobile market that accesses the mobile Internet is between the ages of 20 and 29:

6. More Sophisticated SMS Campaigns – Case Study: Boots  Campaign launched jointly between Boots and one UK based Operator “A”  This method chosen because Boots was convinced that Operator A had a good user base for the type of product(s) they wanted to promote  Campaign was launched purely on and by the mobile channel i.e. Operator A’s network  Target: Single women (i.e. late teens to mid 20s) residing in London – relevant filters applied by Operator “A”  Before receiving the initial Boots marketing message, the target mobile subscribers were asked for their consent to participate  Everyone who replied “Y” was sent the initial targeted message (see screen shot opposite)  Timing: Pre-Xmas period but carried out over 2 stages  Early Dec 2008  Just before X-mas 2008 Note: the campaign did include a link to Boots mobile portal but was centered more on the idea of an “SMS Dialogue” with participants Stage 1: Early Dec

7. SMS Case Study: Boots  SMS were sent between 9 am and noon on a Saturday to coincide with the typical shopping trip timings associated with X-mas period  Participants were given the choice to opt-out after receiving the Stage 1 message  Only 1 in 4 opted to do so  Those who opted in, were sent a targeted message in Stage 2 of the campaign Note: Total response for Stage 1: 13% (Overall result: 1 in 7 Operator A users participated in the Boots campaign) Stage 1: Early Dec

8. SMS Case Study: Boots  Stage 2 incorporated a split by gender  But still concentrated on the “relationship” factor  The same opt-out/opt-in choice was given  Total response rate for Stage 2 was 14% Stage 2: Almost X-mas

9. SMS Case Study: Boots  The campaign was designed to evaluate the appeal of people buying for themselves vs buying for their partners  Generate awareness and sales of two new Xmas fragrance sets: Kate Moss and Diesel  The campaign also highlighted the importance of timeliness i.e. Stage 2 generated a better response as it was so much closer to X-mas  Overall: 70% agreed to receive follow up offers opening up a mobile CRM opportunity for Boots as well as for Operator “A” Note: Men appear more tight-fisted when it comes to spending on their partners…! Stage 2: Almost X-mas

10. Boots Case Study: Some Lessons  The choice of Operator (“A”) was crucial to the success of the campaign  Operator “A” had subscribers which matched Boots target market of single women in a certain age bracket in a given demographic  Same point for single men in a certain age bracket/demographic for “Stage 2” of the SMS campaign  Operator A had the ability to filter these requirements from within its subscriber base and the software to carry out and track these subscribers for the duration of the campaign  In Pakistan, there is only one Operator which has in place an “Information Gathering & Refinement” project by which they can offer “Brands” a set of targeted subscribers to carry out mobile marketing campaigns  As in the case of Boots, the “Brand” will define its target market and the local Operator will match that with its subscriber base

11. Local Operator Target Profile (Shampoo) 30 day active prepaid base (60% youth, 40% higher-age group) ARPU segmentation (PKR 100+) Card reload > PKR 100 Geographic segmentation Top 10 urban cities (sorted by “Shampoo” sale) 16-32 yr old individuals Can we profile “shampoo” users to any SEC/income bracket? (Elicit the concept of buying power) Limit SMS campaign to cities with highest “shampoo” sales Behavior/psychographics…Not applicable in this case

12. Local Operator Target Profile (Broadband Service Provider) Legend: Requirements Customer profiling 30 day active prepaid base: (70% youth, 30% higher-age group) ARPU segmentation (PKR 250+) Card reload > PKR 250 Geographic segmentation (100% users of KHI) Urban youth 15-28 yrs SEC A+, A, B (high buying power) Initial target market: Karachi PSYCHOGRAPHICS - Young, energetic - Mobile - Tech savvy BEHAVIORAL - Avid GPRS user

13. Targeting: Psychographic  Psychographic data: that which refers to the mindset and values of a consumer:  Lifestyle, ideals and behaviour  Or “IAO” variables: interests, attitudes and opinion  Harder to collect than demographic data and more difficult to quantify  In 2009, Carol Taylor (Director of User Experience, Motricity Marketing) identified 5 types of mobile consumers:  Up-to-date: driven to stay current with news, weather, events at all times – want real-time info and looked at as “beacons of information”  Social and curious: “connectors” as they enjoy bringing others together, planning events/outings and networking  Busy and productive: very concerned about info related to their own personal efficiency and their ability to cope with a busy schedule  Latest and greatest: want to be the first to try something even if there is no guarantee that they will be satisfied with it – always want the newest technologies/apps/social networks  Just the basics: not really interested in the phone, except for the fact that it makes life easier – not impressed with new technology – not early adopters and they look for others to review or try tools/apps etc before they think about using the same on their phone

14. Operator-Driven vs Opt-in SMS Marketing  In short-code based SMS campaigns, the entire campaign is Operator independent  It is said to be more “Brand-driven”  Profiling and targeting cannot be worked into the mechanics of the campaign as campaign participation is entirely dependent on mobile users texting in to the short code by their own free will  Operator-driven SMS marketing can yield much better result as the filtering and profiling capability of the Operator allows the brand to target those mobile users who are most likely to participate and fit the target market of the brand  However, profiling capability requires significant investment from the Operator in terms of filtering software (more on this later when we discuss local Operator case study)  In Western markets, many Operators have very strong profiling capabilities and made active use of it as a service offered to brands for mobile marketing purposes