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On-Demand Delivery: Make Retargeting A Part of Your UA Strategy

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On-Demand Delivery: Make Retargeting A Part of Your UA Strategy

How many of your users have your app installed, but never placed their first order? ‘Install’ is not synonymous with ‘acquisition’, and you probably don’t measure the success of your campaigns with the Cost Per Install KPI, but with the Cost Per Acquisition KPI. In this post, we’ll dive a little deeper into the concept of app retargeting as a necessary user acquisition channel.

The user acquisition game plan

App marketers are employing significant resources into user acquisition campaigns. The marketing stack involves a myriad of traction channels such as search engine ads, branded materials (in the case of food apps, supplying take-out/delivery paper bags and restaurant front-door stickers), offline ads like TV and ambient, App Store Optimization (ASO), and more — all of which aim to drive app revenue, brand loyalty, and ideally, increasing app store ranking.

With an install strategy in mind, the overarching goal of performance marketing is user loyalty. Loyalty is defined by users coming back to the app on their own, repeatedly converting and bringing in revenue. Investing lump sums in developing loyalty features or install campaigns won’t be worth anything if the majority of users don’t actually use what the app is for — in this case, ordering food for delivery or pick-up.

Retention and the problem with relying on push

So why bother with app retargeting if you already have push notifications and/or email marketing in place? When it comes to the re-engagement strategy, retargeting falls in the same line with push notifications since both aim for the same goal: get the user back on the app to convert. We want them to successfully sign in and place their first delivery order, and eventually order again (and again).

However, only 53.3% opt-in for push notifications. While relying on just push notifications may have shown improved re-engagement performance over the last few years, a significant portion of the users are still left out from re-engagement campaigns. The same applies to email marketing where open rates average at 20%.

There’s lost opportunity in not reaching all the users who installed your app. So, while you can reach a significant percentage of your audience through these efforts, can you say with certainty that you’ve done all you can to capture potential customers who have shown interest in your service? App retargeting brings advertisers a step closer to maximizing their ability to stay at the top of customers’ minds. Retention, just like acquisition, isn’t a matter of ‘either/or’, but a mix of different growth tactics.

So how exactly is retargeting a user acquisition channel?

The KPIs say it loud and clear: Cost Per Action (CPA), Customer Acquisition Cost (CAC), and cost per incremental first order.

Our clients only measure retargeting success based on these KPIs — metrics defined by app marketers themselves. While user acquisition was conventionally known to end upon app installation, this approach is no longer the case for food delivery and quick service restaurant (QSR) apps. For these apps, an acquisition is successful only when the first order is placed. The order marks the end of the acquisition process.

When the user doesn’t engage in the app — or worse, if they delete it, the investment cost of acquiring them is wasted. The majority of the uplift tests we’ve run for food delivery apps show that the higher volume of incremental conversions come from recent installers. This means that they just needed the extra push to make their first order. Planning retargeting as a small incremental investment to the acquisition budget will drive user lifetime value (LTV) and pays off in the long run.

All forces on the first order

When driving in-app orders, getting the user to order for the first time (activation) is challenging, since it requires them to go through the entire purchase and login funnel. Once activated, a significant portion of users will likely return to the app and place repeat orders (retention).

The likelihood of users coming back to order again has a lot to do with their first experience, so user experience is still paramount for success. Considering the user experience within your re-engagement strategy is key for increasing the loyal users pool. That includes both the experience within the app itself and that of the ad campaign.

A great app that lacks a proper retargeting strategy will likely have lost opportunities. At the same time, a perfect retargeting strategy can’t make up for a poor in-app experience. As app retargeting experts, we have compiled tips in perfecting the creative strategy.

To achieve the long-term success of keeping the user engaged, you’ll need to use:

  • Top-rated vendors: Show the top-rated vendors within ads — taste and delivery time is an important part of the user experience! Don’t gamble with random restaurants; instead, choose the best ones and endorse those.
  • Real-time feed: Have a dynamic product feed that displays only the vendors who are operating in real-time. After all, what is the point of clicking through and having the intention to order, if the restaurant is closed?
  • Geolocation: Match the geolocation of users and their surrounding restaurants that are open for delivery/pick-up. Waiting time is everything these days, hence the ‘money back guarantee’ offered by some services.
  • Deep linking: Bring the user directly to the menu of the very restaurant featured within the ad right after they click on it. Let them skip all the steps and take them straight to the point of interest. This can be done with the proper implementation of deep links and universal links, which are proven to boost performance.

Whether the user ends up ordering from the restaurant that was endorsed in the ad or not is entirely up to them, but one thing’s for sure: app retargeting brings them back at the right time, and as close as possible to the right place (we can’t predict food cravings, but we can certainly influence them).

Allocating retargeting spend from the user acquisition budget

So now you’re ready to retarget, but this question comes to mind: “How much of my UA budget should go to retargeting?”

It depends. Is that budget only for mobile marketing activities? Do you have to split it between install and retargeting campaigns, or is there a broader budget that also includes offline marketing efforts such as TV, radio, and more? What are all your efforts?

Unless your app is getting a significant number of organic installs daily, you’ll have to budget retargeting into your UA cost. How much exactly, depends from app to app. Some do a 50/50 install-to-retargeting campaign split, while others allocate a larger amount for retargeting since their app is already quite established, as they still have to drive the acquisition.

For newer apps, entering the market where brand awareness and market share is low or close to none, you’ll still need to run extensive install and awareness campaigns. That means retargeting would come at a later stage. Here, an 80/20 split is more sensible to start with, which can later be adjusted based on performance goals. That means retargeting needs to come at a later stage when your volume of installs reaches a threshold where retargeting can drive real business impact.

Organic cannibalization isn’t a thing to worry about anymore

“If we’re spending so much money and getting good engagement, is it possible that the retargeting partner is targeting those who would have converted organically anyways?”

For apps that have been investing in retargeting and seeing positive results, there’s always the valid concern of wrongly attributing the conversion or cannibalizing on the organic users (i.e. they would have made an order anyway without the extra push from ads).

Incrementality measurement has become the fundamental way to track and accurately see the value of different marketing efforts. Marketers are able to see the effect of retargeting and other channels using a scientifically-backed method, where the numbers not only prove but show which segments are the most influenced by ads.

Conclusion

Within performance marketing, the terms ‘install’ and ‘acquisition’ are often used interchangeably. For on-demand delivery apps, the acquisition is sealed only when the user has successfully made an order on the app.

By changing the perspective of retargeting as not only a retention tool but also an acquisition booster, marketers will see higher volumes of first order conversions in the long run. Employing tactics like highlighting top-rated vendors, using geolocation, displaying real-time feed, showing relevant messaging, and more, will maximize each conversion opportunity. Finally, by tracking your success with scientifically-based methods such as incrementality measurement, you’ll be able to grow your loyal user pool in no time.

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Retargeting lexicon
Programmatic Advertising

The automated process of buying and selling advertising space through digital platforms.

View-Through Attribution
view-through-attribution

Refer to: Attribution Methodology

Uplift Test
uplift-test

A randomized control trial test conducted by Remerge to measure the incremental impact of one or more campaigns.

See also: Randomized Controlled Trial

Uplift Report
uplift-report

A report by Remerge showing the results of an uplift test. It presents the incremental revenue generated, on top of organic and other marketing-driven conversions. Also contains observed values such as ad spend, group sizes, amount of conversions, converters, and revenues per group, plus other metrics.

SKAdNetwork
skadnetwork

Stands for Store Kit Advertising Network. Apple’s measurement framework for tracking mobile attribution. Introduced in 2018 and widely implemented in 2020 with the iOS 14.5 update.

Segment
segment

A group of users with common attributes such as location, demographics, activity level, value or amount of purchases, and how recently they last opened a specific app.

Retention Rate
retention-rate

The share of users active in the app within certain time frames after install, reengagement, or other events.

Retargeting
retargeting

A type of marketing channel used by an app owner to engage with their existing users through other channels within the same device. Usually, the aim is to encourage users to complete a particular task e.g. completing a purchase, buying in-game currency, placing a first order. The conventional way of retargeting relies on user IDs, such as AAID and IDFA.

Reshuffle
reshuffle

Reshuffle indicates the randomization and marking of users when they were once part of a test or control group.

In incrementality measurement, reshuffling the group assignment for a specific application fights aggregated bias over time where one group doesn't see any ads while the other group is constantly exposed to them.

Reshuffling is relevant in cases where a test has been running for a long time and/or in campaigns the experience more extensive changes to the campaign setups, segmentation, or creative strategy.

Real-Time Bidding (RTB)
real-time-bidding-rtb

The process by which individual ad placements are bought and sold via programmatic auctions that happen instantaneously. With real-time bidding, ad buyers bid on an ad space, which, if the auction is won, instantly displays the buyer's ad. This lets demand-side players such as advertisers or DSPs optimize the purchase of ad placements from multiple sources.

Randomised Controlled Trial (RCT)
randomised-controlled-trial-rct

A method that randomly separates a specific population into two groups that are as similar to each other as possible, namely the test group and control group.

further reading
Queries Per Second (QPS)
queries-per-second-qps

The number of ad placements a DSP is able to process in order to determine on how to bid on them.

Publisher
publisher

Within the sphere of app marketing, a publisher is an App Developer that gets paid for placing ads within their app. For example, an advertiser wants to reach their users via App Y, so they pay App Y to display their ads.

further reading
Public Service Announcement Ad (PSA Ads)
public-service-announcement-ad-psa-ads

An incrementality testing methodology where devices in the control group are shown PSA ads, like donation drives or road safety reminders. By serving real ads, information on the devices within the control group that would have been exposed can be obtained. Unexposed devices are excluded from the measurement to reduce noise.

Probabilistic Attribution
probabilistic-attribution

Refer to: Attribution Methodology

Organic Behavior
organic-behavior

A user’s behavior not directly attributable to specific marketing efforts.

Multi-Touch Attribution
multi-touch-attribution

Refer to: Attribution Methodology

Mobile Measurement Partner (MMP)
mobile-measurement-partner-mmp

Within the sphere of app marketing, MMPs are a service provider that specializes in measuring activities that are happening within and leading to the app. An app publisher may incorporate an MMP into their app to track activity and events e.g. time spent on a certain screen, sources of incoming traffic, app opening frequencies etc.

Lifetime Value (LTV)
lifetime-value-ltv

The amount of revenue generated by the user for the App Developer during the entire duration of the relationship with the user, beginning with the app install.

Last-Click Attribution
last-click-attribution

Refer to: Attribution Methodology

Key Performance Indicator (KPI)
key-performance-indicator-kpi

The key metrics used to assess the effectiveness of an effort in achieving its objective. In programmatic advertising, the common types of performance indicators depend on the goals and nature of each campaign. These can include ROAS, cost per action, and retention rate.

Intent-to-Treat (ITT)
intent-to-treat-itt

An incrementality testing methodology where no ads from the campaign are shown to devices within the control group. Also known as a ‘holdout test’. Cost-free and easy to implement, but with a relatively high level of noise.

This method compares the behavior of all users in both groups. In the test group, this includes both exposed and unexposed users

Incrementality
incrementality

A method of measuring the impact of a specific activity, on top of organic and other activity.

Incremental Revenue (iRevenue)
incremental-revenue-irevenue

The estimated revenue caused directly by the campaign.

Formula:Revenue from test group – revenue from control group = iRevenue

Incremental Return On Ad Spend (iROAS)
incremental-return-on-ad-spend-iroas

A KPI used in calculating how cost-efficient a campaign is. This is used to evaluate the relationship between incremental revenue and the amount of money spent on the campaign. The figure is typically represented in percentage.

Formula:
Percentage: [IRevenue ÷ ad spend] × 100 = IROAS%
Ratio: IRevenue ÷ ad spend = IROAS

Incremental Cost Per Action (iCPA)
incremental-cost-per-action-icpa

A KPI used to evaluate the cost of incremental conversions.

Formula:Ad spend ÷ [test group actions – control group actions] = iCPA

Incremental Conversions
incremental-conversions

The estimated amount of conversions caused directly by the campaign.

Formula:
Test group conversions – control group conversions (scaled) = Incremental conversions

In-app Event
in-app-event

Actions made by a user within the app, such as log-in, registration, completion of onboarding, or purchases. These events can be tracked with the help of an MMP.

Impression
impression

The deployment of the ad to the ad placement. An impression might not necessarily mean that the ad has been viewed.

Identifier for advertisers (IDFA)
identifier-for-advertisers-idfa

A unique random device identifier Apple generates and assigns to every iOS device. Advertisers can use this to track user activity across apps, show them personalized ads, and attribute ad interactions.

Ghost Ads
ghost-ads

A testing methodology that shows devices in the control group an ad ran by another advertiser on the platform, therefore removing any additional cost for clicks and impressions. The control group behavior is then marked with a ‘ghost impression’, which gives the information on which control group users would have been exposed.

further reading
General Data Protection Regulation (GDPR)
general-data-protection-regulation-gdpr

A regulation under the EU (European Union) law on data protection and privacy within the EU and the EEA (European Economic Area), that grants users control over how their data is stored and used by organizations. To comply with GDPR, programmatic sellers must clearly communicate to users how their data will be stored and used. When a user gives consent to an organization to process their data, it enables targeted advertising.

Exposure Rate
exposure-rate

The percentage of devices within a test group that received at least one ad impression, versus the total number of devices within the test group targeted within a campaign during an uplift test. For example, if 900 out of 1,000 users are shown an ad, the exposure rate is 90%.

See also: Uplift Test

Deterministic Attribution
deterministic-attribution

Refer to: Attribution Methodology

Deep link
deep-link

A link that sends users directly to a specific in-app location, instead of the app marketplace. Deep links bypass the steps needed to go through to reach a conversion point, bringing the user directly to where they can perform the intended action e.g. completing a purchase, buying coins, placing an order.

Test Group
test-group

Within the sphere of app marketing, this refers to the group of devices that may be shown ads from a specific campaign in the test. The actions on these devices are then compared to the actions on the devices in the control group.

Compare with: Control Group

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Control Group
control-group

Within the sphere of app marketing, this refers to the group of devices within the target audience that are not shown ads from a specific campaign in the test. The actions on these devices are then compared to the actions on the devices in the test group.

Compare with: Test Group

further reading
Contextual targeting
contextual-targeting

A type of targeting that works with contextual signals only, such as location data (country, city, postal code), language setting, mobile operating system, device model, as well as publisher information.

California Consumer Privacy Act (CCPA)
california-consumer-privacy-act-ccpa

A bill that enhances privacy rights and consumer protection for residents of California, United States. The CCPA took effect on January 1, 2020.

The CCPA provides these rights to consumers:

- Know what personal data is being collected about them.
- Know whether their personal data is sold or disclosed, and to whom.
- Say no to the sale of personal data.
- Access their personal data.
- Request a business to delete any personal information that was collected from that consumer.
- Equal service and price, even if they exercise their privacy rights.

Attribution Window
attribution-window

A specific time frame that is taken into consideration when determining the source of a user’s action.

Attribution Provider (AP)
attribution-provider-ap

A role played by an MMP to credit the in-app activity of users to the correct media sources.

Attribution Methodology
attribution-methodology

Refers to the process of identifying which conversions belong to which preceding click or impression. Common attribution methodologies include:

  • Click-Through Attribution - Determines the source of a conversion based on the user’s click activity.

  • View-Through Attribution - Determines the source of a conversion based on the ad impression delivered to the user.

  • Deterministic Attribution - A model that establishes the origin of a user’s conversion from a specific click or impression, based on unique device IDs.

  • Probabilistic Attribution - A model that establishes the likelihood of a user’s conversion originating from a specific click or impression, based on the data logged on both occasions, such as device language, timezone, IP address, and OS version.

  • Last-Touch Attribution - A model that establishes a match between the action taken by a user (e.g. app open, purchase) and its corresponding ad click or impression. When a user converts from an ad, the DSP that delivered the respective ad is given full credit for that conversion event.

  • Multi-Touch Attribution - Also known as multi-channel attribution. A model determines the value of every touchpoint on the way to a conversion. Rather than giving full credit to one ad, multi-touch attribution divides the credit among all advertising channels that the user has interacted with, leading to the conversion.
Attribution
attribution

A method of identifying the touchpoints a user has encountered within a specified period before making a conversion.

App Tracking Transparency (ATT)
app-tracking-transparency-att

The privacy framework from Apple that, among other things, manages the process of obtaining user consent before accessing their Identifier for Advertiser (IDFA).

App Monetization
app-monetization

The strategy a publisher employs to earn money from their app. This can be done through in-app advertisements, paid membership, and charging for premium features or an ad-free experience, among others. For example, some gaming apps are free to download and play, but users may need to pay in order to progress to the next level quickly.

Android Advertising identifier (AAID)
android-advertising-identifier-aaid

Also known as Google Advertising Identifier. A unique device identifier that Android generates and assigns to every device. Advertisers can use this to track user activity across apps, show them personalized ads, and attribute ad interactions.

Advertisers
advertisers

The advertiser is a person or legal entity focusing on generating sales and leads through serving ads that convey the right message to the right audience at the right time.

In mobile advertising, the advertiser is on the client-side and is the one interested in promoting an app.

Causal Impact Analysis
causal-impact-analysis

A measurement framework developed by Google that works without device IDs. It measures the incremental uplift of one or more conversion events, removing the influence of other campaigns and organic conversions. Used to assess the effect of ID-less campaigns.

Similar to measuring the effect TV ads have, the principle is based on running campaigns on identifiable sub-markets (test group), while leaving other sub-markets unexposed (control group).

Ghost Bids
ghost-bids

An incrementality testing methodology based on Ghost Ads, adapted for retargeting campaigns. The difference is that it removes all devices that are not seen on ad exchanges, or that would not be bid on, from both test and control groups, to reduce noise. A bid is placed as usual for the test group, while the control group is tracked with ‘ghost bids’ (bids that could have been placed, but weren’t in the end).

Return on Advertising Spend (ROAS)
return-on-advertising-spend-roas

A KPI that measures the relationship between the revenue generated by specific advertising efforts and the money spent on them.

Formula

Percentage: [Revenue ÷ ad spend] × 100 = ROAS%

Ratio: Revenue ÷ ad spend = ROAS

See also: Incremental Return On Ad Spend

Supply-Side Platform (SSP)
supply-side-platform-ssp

A company that works with publishers to sell ad inventory across ad networks.

Demand-Side Platform (DSP)
demand-side-platform-dsp

A company that works with advertisers to purchase ad inventory across ad networks. Their platforms are built to identify a desired ad space and place bids on it.

Compare with: Supply-Side Platform

Open RTB
open-rtb

A digital marketplace where ad inventory from multiple publishers are available for advertisers to bid on in real time.

See also: Real-Time Bidding

Self-Attributing Network
self-attributing-network

An ad network like Meta, Snap, and Twitter, that attributes its traffic internally, without the involvement of third-party MMPs.

Variable Bidding
variable-bidding

The dynamic adjustment of bid prices based on a user's in-app behavioral patterns, contextual information, time of day, and ad placement performance.

Dynamic Product Ad (DPA)
dynamic-product-ad-dpa

Also known as a dynamic ad. It is dynamically assembled based on the user’s behavior and information sourced from a feed. This type of ad delivers a tailored experience for individual users.

Real-Time Audience Segmentation
real-time-audience-segmentation

The division of an audience into distinct segments based on real-time events, thus enabling targeted advertising and alignment with a user's behavioral patterns and preferences.

User Acquisition (UA)
user-acquisition-ua

A mobile marketing effort used to attract new users to an app. Paid UA may refer to ads shown in mobile ad networks or social media channels, while non-paid UA involves app store optimization and promotion on the advertiser’s own channels.

Programmatic Advertising
programmatic-advertising

The automated process of buying and selling advertising space through digital platforms.

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