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Mobile Attribution & Marketing Analytics for eCommerce
Mobile Attribution& Marketing
Analyticsfor eCommerce
A Practical Guide on How to Let Data Work for You
Mobile Attribution & Marketing Analytics for eCommerce
Mobile commerce is on a tear.There’s no other way to put it.To name
just one study from the many out there — PayPal-Ipsus research
paper covering 22 countries found that mCommerce is growing at
three times the rate of eCommerce.
Between 2013 and 2016 the compound annual growth rate for
m-commerce is projected at 42 percent vs. 13% for eCommerce. To
put growth in actual sales, mCommerce sales are expected to eclipse
$290 billion worldwide by 2016.
With such numbers, it’s no wonder that usage of shopping apps is
the fastest-growing app category, with sessions on shopping apps
on iOS and Android devices increasing by 174% year-over-year,
including 220% on Android alone.
That’s up from 77% last year as more and more retailers are building
apps on top of their mobile-optimized sites despite the hefty price
tag of developing and maintaining a commerce app.
Introduction
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Mobile Attribution & Marketing Analytics for eCommerce
Mobile Browser vs. App Funnel Metrics
Mobile Browser
Conversion Rate Conversion Rate
App
Products viewed per user
Basket
Purchase Purchase
Basket
Products viewed per userx3.3
x3.0
x1.2
x0.8
Apps also generated almost 50% of mobile transactions for retailers
who have made their app experience a priority. In fact, mobile apps
perform better than any other channel, including desktop.
Why are apps becoming a must-have touchpoint for retailers?
Beyond the fact that mobile is dominated by apps (86% of time spent
on mobile is on apps), there are several factors at play here: speed,
optimal native mobile experience, ability to use mobile payments
and push notifications, not to mention the impact on loyalty and
lifetime value from a user who actually made a commitment to the
brand by downloading its app.
Source: Criteo, State of Mobile Commerce, Q2 2015
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Mobile Attribution & Marketing Analytics for eCommerce
Getting Started with Mobile Advertising Analytics?We recommend reading this first:
THE BEGINNERS GUIDE TO
MOBILE ADVERTISING ANALYTICS
Today’s savviest retailers (online & offline) are embracing big data
as a major facilitator of business growth. Consumer information from
anonymous shopping patterns to cross-channel loyalty programs is
collected, sliced and diced to provide a more relevant and seamless
consumer shopping experience - whether from a brick & mortar
location, the website, mobile site or app.
A key communication channel merchants have with consumers
on mobile is advertising, where relevancy and personalization play
a big part. However, unlike the web, the ability to track, measure
and ultimately optimize app install and retargeting campaigns is
a challenge because of the mobile world’s inherent fragmentation
(different OSs, different environments, different devices).
The good news is that advertising attribution and analytics platforms
utilize sophisticated technology to connect the dots and provide retail
app marketers with rich data to enable smart marketing decisions
across the omni-channel user journey. This guide will cover the latest
of what is possible in this area and how it applies to retail marketing.
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Mobile Attribution & Marketing Analytics for eCommerce
A View From Above
Setting Goals
Defining Key In-AppEvents to Track
Relevant/Personalized Consumer Communication
Smart Consumer Acquisition
Retention & Cohort Analysis
Retention UpliftLTV UpliftROI Uplift
The Bottom Line
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Mobile Attribution & Marketing Analytics for eCommerce
Let’s Dive In
Defining Rich In-App Events that Matter to Your Business
A retail app, as you’re well aware, is one of the
most complex apps to develop. The diversity
of in-app actions that can be taken by
consumers is vast. The ability to track user
behavior on a granular level and then view
aggregated analytics is the basis of making
smart marketing and advertising decisions
across all acquisition and engagement
channels.
It is therefore important that you clearly define
your goals and pinpoint the in-app events that are directly
related to these goals.
Here’s a list of key in-app events in retail apps:
• Login • Wishlist
• Registration • Add to Cart
• Content Viewed (product/category screens)
• Initiated Checkout
• Search String • Purchase
ORDER NOW
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Mobile Attribution & Marketing Analytics for eCommerce
RevenueContent TypeContent IDQuantity Currency
Search StringPriceCurrencyContent IdQuantifyCustomer User ID
Purchase Content Viewed
Diving deeper into the data involves one more crucial step: defining
the right parameters of each in-app event - thus making it “rich”.
For example:
So how can rich in-app events lead to the ability to meet specific
business objectives? Well, if one of your goals is to increase the
number of consumers who bought at least two electrical products,
you’ll want to track the purchase event “enriched” with the quantity
and content type parameters. If you want more women shoppers as
active consumers, you can track the content viewed event in addition
to content type, content ID, quantity and / or search string parameters.
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Mobile Attribution & Marketing Analytics for eCommerce
1
2
Expand your knowledge about your users through deep
analytics
Set the path towards granular segmentation and enhanced
targeting with networks that are at the forefront of mobile
targeting capabilities (those that are able to create advanced
audience targeting campaigns after receiving rich in-app event
data in real time from you or your tracking provider)
Ultimately… by tracking these rich in-app events, you’ll be able to
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Mobile Attribution & Marketing Analytics for eCommerce
Smart Customer Acquisition
So we’ve laid out goals, defined the in-app events that matter to
your business and understood why this data is so valuable.
Now let’s take a step back and recall what advertising attribution
and analytics is all about from a user acquisition standpoint: The
idea is to continue to measure what users are doing inside the app
after they’ve installed it — particularly if these are rich in-app events.
The data is then aggregated to get an in-depth picture of your audience
and which channels (paid or owned), ad networks, campaigns and /
or creatives have led users you want - not just any users - to install
the app.
Measuring Paid Acquisition
Here’s a table that shows which networks did well and which did
not when aggregating rich in-app event data of users who added
women fashion items to the cart.
Networks 4 and 5 reign supreme, while network 2 should be
dropped.
Key takeaway:
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Mobile Attribution & Marketing Analytics for eCommerce
Enabling Lookalike Targeting
By measuring in-app events you can get a clear picture of the types
of consumers that generate the highest value to your brand. You
can then use this knowledge to find users that “look like them” from
a variety of sources by:
1) Increasing spend in a top performing network to maximize reach
of its quality audience (make sure you don’t go overboard and
end up targeting the same users)
2) Replicating the same targeting criteria used by the performing
network with other networks
3) Utilizing the capabilities of the most advanced networks that
support real time data transfer of rich in-app events from a tracking
provider and automatically turn it into a lookalike campaign.
An interesting insight comes from network 5: although it delivered
the lowest number of users, in terms of the install to in-app
action conversion rate, 8.2% is a great figure so an even bigger
investment in this network makes sense.
Another example has network 6 acquiring the largest volume of
users who logged-in and made at least two purchases within their
first two weeks of activity.
Key takeaway:
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Mobile Attribution & Marketing Analytics for eCommerce
Key takeaway:
Measuring Activities on Owned Channels
Leveraging your own assets on owned channels — particularly emails
and phone numbers of your existing segmented consumers who
have yet to install your app — is something you’ll definitely want to
measure, and compare to other channels — including paid ones.
The advertiser's email campaign is doing very well compared to
other channels with the highest conversion rate and the second
highest average revenue per user.
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Mobile Attribution & Marketing Analytics for eCommerce
Key takeaway:
Measuring the Consumer Journey with Multi-Touch Attribution
Another important layer to track in order to optimize user acquisition
campaigns runs higher up in the funnel, and it involves the ability
to go beyond last click attribution. Flawed as giving all the credit to
the network that delivered the last click is, it’s the industry standard.
Which is fine if we look at it from a pure billing perspective.
However, if a marketer is able to see his most common conversion
paths that led users to install an app, he will continue to invest in
these contributing networks. After all, these networks drove your
users down the funnel and made them “sales-ready.”
Network A view
Network A view
Network B click
Network B click
Network C click
Network Dlast click
Network Dlast click
1,500 installs
900 installs
Let’s explore the following scenarios:
Network C plays a key role in driving installs
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Mobile Attribution & Marketing Analytics for eCommerce
Measuring (True) Omni-Channel LTV
The proliferation of mobile devices, on top
of web and brick & mortar touchpoints
have created an amazing opportunity for
omni-channel retailers. However, it has also
generated a massive challenge of connecting
the dots to provide a seamless and consistent
user experience.
By using a server-to-server integration you
can measure the actions acquired app users
take across touchpoints (assuming they
are logged in to enable matching via their
consumer ID), giving you the true value
generated by the acquiring ad network.
U.S. Cross-Device Share of eCommerce Transactions
% of users who used multiple devices in path to purchase
41%
37%
43%
User completed purchase on:
Smartphone
Desktop
Tablet
Source: Criteo, State of Mobile Commerce, Q2 2015
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Mobile Attribution & Marketing Analytics for eCommerce
Let’s look at the following example to illustrate this point:
Disconnect
"I clicked on an ad that led me
to install an app after which I've made 3
purchases"
"Sadly, my LTV is only
$50
"When it's all
connected I'm worth $350!
Connected
Key takeaway:The value an ad network provides omni-channel retailers is often
much higher than they think. Best of all, you can track it to see it.
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Mobile Attribution & Marketing Analytics for eCommerce
Measuring the Impact of TV Ads
As app marketers drive user acquisition through DSPs, SSPs, Google
AdMob, Facebook, and a whole slew of mobile channels, they’re
realizing that mobile as a channel is becoming saturated, overly
competitive and even limited in reach. One channel they are turning
to for help is television.
The fact is TV is still very much a part of the fabric of our lives. According
to Nielsen’s 2014 Q4 Report, there were 285 million TV viewers in the US
so running a TV ad campaign guarantees access to a mass audience.
Digital video platforms have a long way to go to catch up.
The good news is that even while watching TV, a viewer’s smart
device is only an arm’s length away. In fact, Nielsen found that 84% of
US viewers are watching TV with a second screen in hand. Sixty-four
percent of viewers are using their smart device simultaneously. It’s a
great opportunity to capture their attention to download an app on
the spot or incentivize inactive users to take action.
View ad for 'Famous Footwear' mobile app
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Mobile Attribution & Marketing Analytics for eCommerce
How does it work? Basically TV syncing providers offer detailed
information on the exact time a TV ad was aired. A tracking provider
matches that data which is provided in real time with installs and
attributes credit to the TV network, assuming it occurred within a
predetermined time frame after the ad ran (usually within minutes
to a couple of hours at most).
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Mobile Attribution & Marketing Analytics for eCommerce
Measuring Shopping via Social Networks
A new form of online shopping that’s creating a lot of buzz as of late
has to do with ’Buy’ buttons, as social platforms — including Facebook,
Instagram, Pinterest, Twitter and Google — have all announced plans
to offer this service.
How does it work? A user enters his credit card number into the social
app, along with his shipping details. When he later sees something he
wants to buy, he can click on the “Buy” button, which then informs
integrated retailer partners where to ship it.
This form of one-click shopping has great potential and offers another
way in which retailers can acquire new customers — although probably
not new app users as it doesn’t involve any app install. However, the
merchant can always encourage them to install the app once they
are in his database.
In theory, when and if this functionality takes off, measurement is
rather straightforward. The social app can send an in-app event to
the analytics company (usually requires a special integration of its
own to select providers), which is actually a deeplink with metadata
on the actual purchase.
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Mobile Attribution & Marketing Analytics for eCommerce
Relevant & Personalized Consumer Communication
The digital age consumer expects nothing short of a seamless
experience as she constantly moves back and forth across online
and offline brand touchpoints. Any glitch and you risk losing her to
a sea of competitors eager to take your place.
The good news is that this consumer also perceives behavior-
based communication as a service rather than an annoyance and is
comfortable with sharing information in exchange for personalization,
according to a newly-released and comprehensive mybuys report.
60%
60%
58%
58%
50%
I'm comfortable having my shopping interests and behaviors used
by retailers...
In order to expedite my shopping experience on site
So they can deliver relevant offers throughout the year
In return for a more personalized experience
As I believe I will receive a better overall experience
To coordinate a better shopping experience across the channels I use
The report also found that 52% of consumers spend more money
when they receive a truly personalized and consistent shopping
experience.
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Mobile Attribution & Marketing Analytics for eCommerce
Mobile, which is already playing a huge role across the consumer
journey (both in the research and purchase stages), is no exception.
Whether through email, coupons, push notifications or advertising,
personalized and relevant communication on mobile devices is
paramount to success.
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Mobile Attribution & Marketing Analytics for eCommerce
Retargeting Enablement, Attribution and Analytics
First things first: a must-have element in a retargeting campaign on
mobile is deeplinking as you’ll want to direct users to specific app
screens. It’s a no-brainer.
Second, there’s the issue of transferring data to a retargeting network
based on the level of integration you or your analytics provider have
with the network, as follows:
Data on standard in-app events can be transferred ‘manually’ in lists
(for example, a list of IDFAs of users who viewed products but didn’t
buy). Once a list is created, however, it cannot be changed.
Here we have two types:
1 Basic integration: Sending standard in-app events in real time to
enable segmented retargeting. For example, users who added a
product to cart but didn’t buy. In most cases, these integrations
can only support a name parameter (but at least a user in that
segment is ‘dynamic’ and will automatically be part of a different
segment once he purchases).
2 Advanced integration: Sending rich in-app events in real time to
enable personalized retargeting on a ‘segment of one’ (e.g. a
user with IDFA 1234 who viewed product 777 can be shown a
creative with product 777 and relevant messaging; you can even bid
higher for that user if, for instance, he has a high LTV). Currently, the
number of networks that can support such an advanced integration
is still limited but more and more networks are following suit.
Static:
Dynamic:
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Mobile Attribution & Marketing Analytics for eCommerce
When it comes to retargeting attribution, the mechanism is no different
than an install. It simply means an advertiser defines a desired in-
app event (e.g. app open for a dormant user, in-app purchase for an
existing user) for which the attribution provider would credit a media
source that delivered the last click that led to the desired action.
Retargeting attribution is often divided between “re-attributions”
and “re-engagements.” The former represents users who re-installed
the app after interacting with a retargeting campaign (assuming the
IDFA/GAID remains the same), while the latter describes users who
have the app installed and engaged with a retargeting campaign.
Once tracked, aggregated data of all users will help you pinpoint the
best performing retargeting networks, campaigns and creatives in
the same way that was illustrated in the acquisition campaigns above.
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Mobile Attribution & Marketing Analytics for eCommerce
Enabling & Measuring Facebook Custom Audiences Campaigns
Back in May this year, Facebook announced that as of November 4, its
advertising clients will no longer be able to access device-level data
from their Facebook mobile app install campaigns.
The good news is that the social network’s Mobile Measurement
Partners will still have access to this data, which means you’ll still be
able to use it in your Custom Audiences campaigns. This is done by
configuring the campaign in Facebook which will run automatically
when it receives rich in-app event data from the measurement partner.
Measuring Location-Driven Retargeting Campaigns
According to a Google-Ipsos report, 4 in 5 consumers want ads
customized to their city, zip code or immediate surroundings. The
report also found that 50% of consumers who conducted a local
search on their smartphone visited a store within a day while 18%
actually bought a product. That’s why targeting consumers while
on-the-go has tons of value.
Tracking location is possible
by Lat/Long parameter. The
advertiser can add these
params to each in-app
event which can be sent
to the networks that support
rich in-app events. You’ll then
be able to understand where
consumers take specific types
of actions.
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Mobile Attribution & Marketing Analytics for eCommerce
Measuring Bluetooth-Based Beacon Technology
With beacon technology, retailers can pinpoint a user’s location
and send relevant content based on where consumers are. Since
bluetooth connections actually work indoors unlike GPS, it captures
an audience that’s highly likely to engage with the messaging while
in the immediate vicinity of a store or, unlike GPS, in store.
Sending a push notification is ideal if the user has the app installed.
If not, an SMS will also work well. Sending an ad while in-store can
work by offering a user an immediate discount for installing the app
(requires sending of real time attribution data to enable opening of
the specific campaign app screen after deferred deeplinking).
Measuring a beacon-driven campaign - whether using Apple’s iBeacon
or Google’s brand new platform-agnostic Eddystone platform and
recording events in your server - involves defining in-app events and
reporting them to your analytics provider.
You can then use cohort reports t o
measure which group of users from
which campaign had the highest
engagement with beacon messages.
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Mobile Attribution & Marketing Analytics for eCommerce
Measuring Direct Marketing Efforts
Direct communication with consumers mainly over owned channels
is the key to a strong consumer-brand relationship. All you have to
do to measure these campaigns is set up a tracking link and then
compare your different channels — paid or owned.
Email Campaigns: According to research by Forrester, 42%
of retailers' email messages were opened by consumers on
their smartphones and 17% were opened on tablets. So you’ll
definitely want to measure email engagement and more
importantly what follows. With proper deeplinking in place,
you can direct users to specific app screens from the mobile
web or email app.
Push Notifications: Push has gone mainstream. That’s the key
takeaway from the following highlights of a study by Urban
Airship:
• Retailers sent 34% more push notifications in 2014 compared
to 2013
• Consumers’ engagement rate with push notifications in the
2014 holiday season doubled compared to 2013
• More than one-third of all retail app opens were the result
of a push notification
Coupons: The number of adults who redeem coupons via a
mobile device is expected to jump from 78.7 million to 104.1
million between 2014 and 2016, according to eMarketer. With
such volume, it is important that retailers offer the best overall
experience to optimize usage.
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Mobile Attribution & Marketing Analytics for eCommerce
Creating a Unified User Experience for Optimal Results -
Ideal for Direct Messaging
Overcoming the challenge of a fragmented mobile space with multiple
channels to create this elusive seamless communication with prospects
and existing consumers involves five components:
1) Smart Links: Advanced technology can make your life much
easier by allowing you to configure a single tracking link per
campaign for all sources. This smart link automatically detects
where the user is and where he needs to be directed as he
engages with the campaign. So instead of configuring at least
five tracking links for iOS, Android, Windows, Amazon and
web, all you need is one. That means there’s a lot less room
for error - be it broken links or links that end up taking your
users to the wrong place.
2) Deeplinking: Connecting the web-to-app and app-to-app
environments, while supporting the opening of a specific app
screen.
3) Deferred deeplinking: The ability to identify whether the
user has the app installed on his device or not and if not, to
take that user to the app store where he can download the app
4) Real-time attribution data: Enables the opening of a specific
landing page after deferred deeplinking and upon first app
launch.
5) Utilizing customer user ID to re-engage with the consumer
in way that reflects her specific actions across the different
channels.
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Mobile Attribution & Marketing Analytics for eCommerce
Let’s explore two examples:
1) Email offer to a consumer who has the app installed:
NEWCOLLECTION!
2) SMS to an existing consumer who does not have retailer’s
app installed:
Email promotion for new iPhone on sale
SMS with deal on new collection
Redirect to the right app store
Specific landing page of new collection deals
SmartphoneGmail app iPhone product
page in smartphone app
iPhone product page in tablet app
iPhone product page in desktop app
Tablet web
Desktop web
Download App Launch
Single Smart Link
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Mobile Attribution & Marketing Analytics for eCommerce
How to Keep Consumers Coming Back for More
Retaining consumers to foster a lasting consumer-brand relationship
and ultimately maximize their lifetime value is perhaps the most
important goal for a retailer. The problem is that it’s also the most
challenging… So what can you do to get retention right?
There are two main strategies here: first, product-related. It goes
without saying that your product must provide a top notch user
experience. Any unnecessary friction and you risk losing the valuable
consumers you worked so hard to acquire.
Second, advertising-related, which is what we’ll focus on. Specifically
we’re talking about retention and cohort analysis.
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Mobile Attribution & Marketing Analytics for eCommerce
Retention Analysis
The more straightforward analysis involves the retention report. It
is calculated as the unique number of users who were active on a
specific day/week out of the total number of unique users who first
launched the app in the selected timeframe.
Depending on how deep the granularity offered by the analytics
provider is, you can check the retention of users from a media source,
campaign, ad group, country, city, OS version, device brand, device
model etc.
Let’s explore the following case study of a leading retailer, broken
down by campaign:
Key takeaway:• Campaigns 1 and 4 performed well across the board, retaining
12-14% of users on day 12.
• Campaigns 2 and 3 underperformed from day 1, retaining only
5-7% of users on day 12.
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Mobile Attribution & Marketing Analytics for eCommerce
Optimization performed on campaigns 2 and 3:
• Budgets reduced
• Targeting & messaging modified to better reflect campaign 4
• Low performing ad sets within the campaigns were shut down
The data from a couple of weeks later clearly shows the advertiser’s
efforts paid off:
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Mobile Attribution & Marketing Analytics for eCommerce
Cohort Analysis
Retention only tells us how many users who launched the app during
a set timeframe reopened the app in the days that followed. Cohort
goes much deeper. Let’s take a step back to explore this strategy.
A cohort report enables you to group users with common characteristics
and measure specific KPIs over different timeframes. It offers a
really good indication of the quality of the average customer and
whether it’s increasing or decreasing over time. The metric - whether
sessions, revenue, or any other defined in-app event - is calculated
per different timeframes, which represent the first X activity days per
user, and then accumulated among all users (that’s why the graph
never drops).
Here’s an example of how a cohort analysis can
boost retention and lifetime value by increasing
the average number of sessions per user. In this
case, the cohort was grouped by the media
source that acquired the user (other examples
include campaign, publisher,
ad group, geo etc.)
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Mobile Attribution & Marketing Analytics for eCommerce
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
A
B
C
D
Cohort graph as seen on May 1:
Average Sessions Per User
Days
Key takeaways:
• Network A starts off with a bang, producing high quality users
that are highly active in the first 14 days after which the growth
rate begins to plateau
• Network B is also delivering quality users showing a modest yet
steady climb throughout the period
• Network C is slowly growing until day 7 but then flattens
• Network D performed poorly - not only did it acquire low quality
users that barely engaged with the app, it also did not show
any improvement over time.
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Mobile Attribution & Marketing Analytics for eCommerce
Optimization performed:
• Having noticed the drop on day 14, the retailer began retargeting
its users at that time to encourage them to continue engaging
with the app
• The budget of Network B was increased hoping it would generate
more users who would only increase their engagement over time
• Network C was broken down to the campaign and ad level and
those that underperformed were removed
• Network D was removed
Cohort graph as seen on June 1:
Key takeaways:
• Network A retargeting worked well as consumers continued
engaging with the app at a growing rate beyond day 14
• Network B continued to deliver quality users (the increase is not
seen in this graph as it shows the average sessions per user, but
it can easily be viewed in the report that measures quantity)
• Network C optimization worked well as the engagement growth
rate improved compared to the previous month
A
B
C
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Days
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Mobile Attribution & Marketing Analytics for eCommerce
As more and more retailers are embracing mobile as a central
if not the most important component of their strategy, they
are moving beyond mobile-optimized sites to develop native
apps. Despite the fragmentation and the challenges it creates, the
mobile world is rapidly evolving (and that’s an understatement),
catching up with the web when it comes to measurement, analytics
and ad optimization capabilities. Retailers who are ready to take on
this brave new world will reap the rewards.
To Sum Up
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