1. Mobile Marketing ANSHU SHARMA IIFT 17TH JAN 2015
2. Scope Traditional Telco Mobile Marketing Feature Phone
Marketing Channels Gratification Business Case Mobile App Marketing
Channels Suggested Example Video Mobile Market Automation
Segmentation, A/B Testing, In App & PNs Campaigns Analytics
& Data Ecommerce Market Tracking Sheet & KPIs Deep Linking
Cohort Analysis
3. Mobile Ad Landscape
4. * Includes: Ad Networks, SSPs, Private Exchanges, and Ad Rep
Firms ** Includes: Media Agencies, Creative Agencies, Trading Desks
*** Includes: Ad Exchanges and DSPs This slide represents Display,
Video, Mobile based on Rare Crowds Analysis of Advertising
Ecosystem Impression / Dollar Flow Note: Ad Servers, Yield
Management Systems, Analytics, DMPs, etc Take out about 8-10% of
spend in total as they pass through the ecosystem 20% ADVERTISER
AUDIENCE Agency* * Keeps 5-25% Large Publisher (Direct Reserved
Premium ) Keeps 75-95% Large pub (Remnant) Keeps 40-80% Publisher
Aggregat or* Keep 10-80% (May include multiple vendors) Small- Med
Publishers Keeps 20-60% 65% 25% 5% 20% 25% 25% FLOW OF ADVERTISING
IMPRESSIONS (US) Percent impressions 40% 35% 40% 35% Ad spend 100%
Exchang es, DSPs *** Keeps 10-20% (may include multiple vendors)
FLOW OF AD SPEND (US) Percent Dollars Captured (in yellow) 25% 5%
PerImpressionPriceDrops 4
5. Communication Platforms for VAS Promotions VAS PROMOTIO N
PLATFORMS SMS Out Bound Dialing EOCN/USS D CELL INFO PLC Cross
Promotion IVRS SELF CARE START- STOP RETAIL/ Go to Market
6. Most Popular Communication Platform Advantages Cost
effective , Fast n Easy & Reliable Perception Considered
intrusive, irrelevant Can be leveraged by Base Segmentation
Vernacularisation Timelines Over 65% customers prefer to read promo
SMS on Sunday/Holidays; Weekdays are not proffered especially
Monday & Tuesday Customers would also prefer Promo SMS after 5
PM SMS
7. Tagging Promotions on Activation and Deactivation messages
across related / unrelated product categories Behtar Zindagi 55678
IVR be promoted as a tag promo on Deactivation message of Mitti Ke
rang Behtar Zindagi promo can be tagged with on MT Charging SMS of
Talk to Me Tagged promo on Activation Confirmation of a related /
untelated VAS category across other VAS Content providers. Behtar
Zindagi Can be tagged on LAPU Conf SMS on IFFCO Base Explore
possibilities of tagging promo on HT Song Change Confirmation SMS
to Rural base Tagged Promo on Service messages - Roaming ; Users
usually read sms received during travelling and a far likely to try
a service AFC from Altuist can be promoted on Drop over message on
Raat Baki IVR of Hungama Friend Locator is likely to get better
conversion if tagged with PLC content of Friends Chat. PLC Cross
Promotion
8. POP Material in the rural market. Nearest Grain/ Vegetable
Markets. Incentivize Retailer on activation of VAS through PEF/SEF
POP Material at IFFCO Retailers for VAS Targeted at Rural base POP
Material at Youth Hangouts for Youth centered VAS Festive
gatherings, Religious gatherings, Agro Fests or and related events
attended by rural folk Branding on Public transport Branding on
Public carriers POP at Weekly Bazaars Celeb Endorsements on radio
and RJ mentions Radio Contests Cinema Advertising / Brand Branding
on Transport used by FOS and Incentive on conversion Buzz on Social
Media through Celeb endorsements, Winners of Various Contests
RETAIL/ Go to Market
9. Telco/VAS Marketing Plan: Gratifications Operator Subscriber
Base of UPU Airtel 18,055,029 Airtel Rural Base in UPU 9,930,266
Avg Price point @ Rs15, Total Revenue/ Month 72,300 1,084,500
Activity Conversion Number/day USSD Promotions,4 hrs/ 30,000 300
Cell info, 1 week/ 2,40,000 1,000 SMS push of Toll number - 1 lacs
sms for 1K calls 100 Ground Activity - 10 OBD from Airtel End:
300,000 => 4000 Subs 1,000 Monthly Subscription 72,300 Total
Airtel Revenue 1,084,500 Company Share @ 36% - Earning 0
Gratification Cost 10% of Handygo share 0 Company Share 0 Projected
Subscriber Monthly Projected Revenue (INR) 289200 2,892,000 Airtel
Share Share @ 66% 1,908,720 Company Share @ 36% - Earning 983,280
Gratification Cost 10% of Handygo share 98,328 Company Share
884,952 Operator Subscriber Base of UPU Rural Base in UP 1st Month
Penetration 2nd Month Penetration 3rd month penetration 4th month
penetration 5th month penetration 6th month penetration Airtel
18,055,029 9930265.95 29791 49651 69512 99303 129093 158884 Avg
Price point @ Rs20 595816 993027 1390237 1986053 2581869
3177685
10. Mobile Marketing Non Feature Phones The Telco managed
mobile Marketing SMS - Short Codes Outbound Dialer Long Codes USSD
Customer Self Care Portal - *121# Cell-id based Broadcasts IVRs
Missed Call Alerts In Message Advertisement An Example Behtar
Zindagi
11. Mobile Marketing Mobile Website / Native App strategy
Location Based Marketing Permissions / Preferences
12. Appstore Optimization : ASO Keyword optimization (KWO)
Keyword Optimization (also known as keyword research) is the act of
researching, analyzing and selecting the best keywords to target
and drive qualified users from app stores to your app. App store
optimization tool provider Sensor Tower also breaks keyword
optimization down into three parts: relevance, Difficulty Score and
Traffic Score.[16] Conversion rate optimization (CRO) Conversion
rate optimization involves all metadata available and publicly
accessible in the app stores, like icons, screenshots, description
and update texts.[17][18] This part of app store optimization is
responsible to convert the traffic acquired through keyword
optimization into app downloads. Location labs Appstore
Optimization Slides
13. The Keys to Mobile Marketing Usability Do you have a mobile
optimized site? Do you have a native mobile app? How many steps
from search to purchase? Trust Do you have a user rating? Are
people talking about your brand online? Personalization Are you
finding you customer at the right time? Are you reaching your
customer in the right place? Are you targeting your customer with
the right message?
16. WOWOKAY, SO HOW AM I GOING TO DO THAT ? DO WE HAVE A
DEDICATED MAN SITTING BEHIND AND OBSERVING LIKE WE ARE DOING IN
THIS VIDEO?
17. Challenges Location Where am I ? Office or Home or my shop
? Personality/ Personas If I love to camp or play football ? Which
Segment? How do you know my existing products, my brands and what
needs replacement ? How do you know if I look for expensive brand
or a less priced ? How do you know that I would love to fly as a
second alternative ? How come an app knows that I could make
payment through my mobile? What happens to my privacy ?
18. How is a mobile marketer going to make all these rules?
Should I map the Customer Journey ? Event based Rule engine should
do ? How many such rules would be required to monetize the moments
of truth ? Is it feasible ? YES Lets Make some Rules -
Exercise
19. Mobile Market Automation Aspects Segmentation PUSH In App
Campaigns A/B Testing Analytics & Data
20. Automated A/B Testing Experimenting Options Available w.r.t
every touch points with the customer in terms of Message Content UI
elements Run the experiments on consumer segments to target based
on Location, device type, app version, traffic source, and in-app
behaviors. Add your own Attributes and events specific to the
particular brand app Running concurrent experiments on the Fly
21. Event-Based Triggers Behvior Triggers Add to Card Card
Abandonment Checked a Product /discount items Has Shared socially
with friends Life cycle Based New User Repeat Customer About to
Churn Calendar Events Real Life Event Instant Gratification
Entering a Mall/Shop
23. custom in-app message templates to drive higher user
engagement.
24. Dynamic Targeting Send highly personalized messages to
specific customer segments geography, device type, app version,
traffic source, custom user attributes, and in-app behaviors
25. Native Ads How and ROIs TBD For Reference Snap Deal
Marketer http://appiterate.com/usecases.html
26. App Widgets Mobile Screen Real Estate TBD
27. Ecommerce Marketing Tracker Marketing Spend: Visitors to
the website/ Mobile /channel Orders / channel Orders / Customer:
How many orders does a customer submit, who was first attracted
through this channel. This KPI is influenced by other factors as
well, but gives you an initial feeling for the customer quality. It
is up to you how you define lifetime (1m/6m/1y). In a later version
I will go into CLV management more deeply. Revenue/ channel
Discounts Needed/ Channel
28. Are these KPI Useful ? What do I do now? Basket Size
(Basket): How much revenue did this channel generate per order. It
helps you to understand the economic value of the customers that
you attract through the different marketing channels. Conversion
Rate (CR): How many customers per 100 visitors, that came to your
site, finally ordered a product? The Conversion Rate helps you to
understand if people that came through this channel only browsed
around, or actually purchased something. Cost Per Order (CPO): How
efficient is this marketing channel? The cost per order tells you
how much you spent to generate one order. Real Cost Per Order (real
CPO): To be able to compare channels on a CPO basis (which channels
generates the cheapest customers), the CPO should be adjusted by
certain factors. One big influencer is the discounts you needed to
give to generate an order. E.g. flash sales are usually relatively
cheap to initiate, however you need to give huge discounts. This
increases the adjusted (real) CPO accordingly. Customer Lifetime
Value (CLV): How much revenue does a customer that is generated
through this channel generate for you. This factors in the average
basket size, as customers that come through different channels
reorder differently, and spend different amounts. Return On
Marketing Investment Factor (ROMI Factor): How much revenue did you
generate per dollar invest? It helps you to understand the return
per marketing channel. It is already adjusted with discounts to
compare the factor cross channel. If you want you can adjust the
factor by other influencers.
29. Exercise Abandon Cart? How do I retarget ? Rules Time
Duration after someone traversed and left Message Method Discount
Segment Timing
30. Attribution Modeling A NECESSITY FOR CONVERSION
STRATEGY
31. Last Touch Model Measure - What was the last touch point
the customer interacted ? What is the conversion % for each last
touch point ? Generally, Email is considered the greater impact for
sales conversion
32. First touch Model Measure What % of the consumer use which
channel as First touch or the first interaction or the first
keyword (in direct search) What is the impact % table for each
touch point in FTM ? FTM works as a strategy tool for Social Media
marketer
34. Customer Credit Sharing Engagement Factors Click on Ad
Simply Viewed In Video Banner Ad Media Factor Std Ad Animated Ad
Size of the Banner Ad Time Factor Time span between ads viewing
& conversion Position Factor Position the offer/ad conversion
%
35. Attributions Model -Campaign Measurements & Results
Which Ad channels drive the best results ? How are these channels
influence each other ? Which mix of ad/market spend on these
channels works best ? What kind of creative ? What size, placement
& frequency drives the consumer behavior ? Basically what
tactics works best for your business !
36. Custom Credit Rule Examples What are the customer credit
Rules that works best and leads to conversion. It could be a series
of interactions before the moment of truth Mapping the Offer/Ad
Interaction Maps and conversions provides the best media/campaigns
budgets.
40. Analyzing the Cohorts On Boarding Trend, the orange left
arrow, indicates the products effectiveness in its first month of
use and its trend over time, which is nothing less than a metric
for user on boarding effectiveness. The first cell in each column
indicates the monthly active rate for the cohorts first month as
users. In our hypothetical data set, that numbers growth varies
from 35% to 41% over time. The product team has done a reasonable
job of improving user on boarding and engaging users when they sign
up Longitudinal Trend, the top red arrow, indicates how the
activity rate changes as users continue to use the product. The
first row is the oldest cohort of users with the most recent data,
the ones who signed up most recently. The bottom row is the newest
cohort. Time flows right in this chart.
41. Cohort Analysis Average Revenue Per Customer Over Time -
Chart monthly revenue over time to contrast with cohort data
Individual Channel Growth Over Time - Chart all accounts to
visualize trends. Number of Customers in Each Cohort - Chart number
of customers in each cohort to see how sensitive cohort data is to
sample size and also see the size of the new customer pipeline over
time. Average Monthly Revenue By Cohort - Chart the revenue by
cohort to see if newer customers generate more or less revenue than
older customers. Really good for marketing spend evaluation. Cohort
Comparison - Chart the different cohorts over time to see how their
revenue characteristics compare.
42. Why Deep Linking Matters ? Links in email/sms not prompting
the user to open the native app and straightway opening a browser
Quite prominently seen in most of the apps Ecommerce Alerts
providing the Access to Purchase, however not taking directly to
Purchase page or CTA landing page Asking to login on a portal Ebay
and not taking to PDP ETSY has fixed it and fixed the revenue
leakage as well Marketing links automatically detects the presence
of app and auto- matically takes to either browser or app Gaming
Apps can save the session today, however they can include the saved
sessions in the PN and straightway take it to the that level In App
/ PNs directly translate into revenue TW Cards / Google App
Indexing / FB App Link Tags
43. Deep Linking is Context Critical for Mobile Marketing ADs 2
App SMS 2 App QR 2 App EMAIL 2 App WEB 2 App SOCIAL 2 App App 2 App
Landing Page Optimization Strategy per traffic source. Cohorts /
Traffic Source would enable to fix the leakages and marketing
campaigns improvement
44. Good Read on Deep Linking
45. Investment Landscape
46. Merging the Old & the New World Browser Cookie Data
Management - DMP
47. Data Management Platform ( DMP ) A very smart, very fast
cookie warehouse with analytical firepower to crunch, de-duplicate,
and integrate your data with any technology platform you desire
Demdex (now owned by Adobe), RedAril, and Krux are what I would
consider pure-plays, while Lotame, Collective, and Turn provide
services
48. DMP Information flow
49. Multi Channel Data Aggregations@DMP
50. Cookie Match Companies LiveRamp, DataLogix, Datran,
TargusInfo, Acxiom
51. Ad Cookies Step by Step A request is sent from the browser
to retrieve an ad from the publisher network. The publisher network
retrieve a number of variables from the publisher - in some
exchanges the publisher chooses which data it wants to share.
Publisher variables include: Anonymity (if anonymous URL above is
not shown) URL e.g. youtube.com CookieId (buyers can use this to
match the user to a pervious seen user, e.g. for a remarketing
campaign) Vertical - e.g. Videos > Sport Blocks - e.g. no Google
Chrome ads please Location - e.g. user is in UK, London
52. Ad Cookie Step by Step The network then sends out a request
to the buy-side to find ads e.g. a request is sent out to the DSPs
and Buyer Networks. This includes the publisher variables that are
set in the request sent to the exchange. The DSPs and BuyerNetworks
then run a query. SELECT snippet, bid FROM all_advertisers WHERE
targeting_url = request_url Bids are then returned by the buyers
within the 120ms threshold. bidder_A: Advertiser: amazon.com CPM:
$2.50 bidder_B: Advertiser: ebay.com CPM: $0.50 The winning ad is
then selected. The ad is sent back to the users browser. The buyer
often pays the second highest price to the buyer.
53. Real Time Bidding User visits a website: say abcd.com.
Within abcd.com there is a HTTP request to SSP, to fill an ad slot.
On receiving the request for showing the ads, the SSP conducts a
real time auction. To each of the DSPs whose have expressed
interest in this user (some SSPs may be willing to show ads to
users from a specific geo, some may be willing to show ads on a
certain website, a retargeting DSP may be willing to show ads to a
predefined set of users etc.) The SSP sends a bid request. The bid
request looks like this: [ "auction_id": 1234abcd, "geo":
"Bangalore, India", "ad_width": 728, "ad_height": 90, "website":
"abcd.com", "id": ssp1234 ]
54. Real Time Bidding Demand Side .. On receiving the bid
request, each DSP needs to send a bid response. DSPs typically
calculate bid response based on the parameters in bid request (geo,
banner size, etc) and the user profile that DSP has stored for user
id dsp1234 (Remeber that ssp1234 was mapped to dsp1234 in cookie
mapping stage, and data provided by DMPs is stored against the key
dsp1234) Bid response looks like this: ["auction_id": 1234abcd,
"bid_value": 12.34 "adTag": ""); " ]
55. Real Time Bidding Awarding the Inventory The SSP compares
the bid response of each of the DSPs, and awards the impression to
the highest bidder. These auctions are usually second price
auctions: the highest bidder wins and cost to highest bidder is
second highest bid in the auction. The SSP redirects user browser
to the ad tag provided in the bid response, which renders the ad to
the user's browser.
56. APPENDIX
57. Reference Digital Marketing Periodic Table for Lingo &
KPIs
58. Players Adobe Marketing Cloud Appboy Appiterate Artisan
DeltaDNA Kahuna LeanPlum Localytics Nudge Playfab Playnomics
PushSpring Scientific Revenue Silverpop Swrve Tapjoy (via 5Rocks)
Tapcrowd Upsight (formerly Kontagent) Urban Airship Which mobile
automation features do you use? *This question is required.
Targeting Cohort analysis/user profiles Segment targeting
Retargeting app users outside of your app Targeted in-app rewards
or incentives Analysis A/B and/or multivariate testing LTV tracking
Real-time analysis Surveys, ratings, feedback Messaging Push
notifications Email campaigns SMS campaigns In-app messaging
Location-specific behavior/messaging Optimal time, delayed, or
flexible messaging Engagement Personalizing app content
Personalizing app functionality and/or gameplay Promotions and/or
sales
59. Acronyms Eng. Rate Engagement rate. For promoted tweets on
Twitter, engagement rate is calculated by dividing the number of
engagements a promoted tweet receives by the number of impressions.
Follow Rate For promoted tweets on Twitter, follow rate is
calculated by dividing the number of follows by the number of
impressions within a campaign. Form Submits Form submissions on a
website. These metrics indicate what percent of form submissions
come from each digital marketing source (e.g. paid search and
referral traffic, email campaigns, social media). Gross Open Rate
The number of times an email message is opened, either by the
original recipients or by those to whom the recipient forwarded the
message, divided by the total number of delivered messages. Also
known as total open rate. Like Rate Facebook page like rate. The
number of page likes divided by number of impressions per ad. MQL
Marketing-qualified lead. This is a lead that Marketing has vetted
and passes on to Sales. RL Raw lead. This is a lead that has not
yet been vetted and accepted by Marketing. SQL Sales-qualified
lead. This is a lead that has been passed on to Sales from
Marketing, and accepted by Sales. Unique Open Rate The number of
unique recipients that opened an email message divided by the total
number of delivered email messages. This measure does not count
multiple email opens by a single recepient