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A complete guide to user segmentation for delivery apps

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A complete guide to user segmentation for delivery apps

How many more orders would your customers make if they were shown the right ads at the right time? What are the effective ways to drive customer loyalty? How can you incentivize a customer to come back to your app after they have lost interest?

By understanding the buyer journey and knowing where your customers are in the funnel, you can design high-converting ad campaigns through relevant messaging. An effective segmentation strategy is essential in achieving better conversion and retention rates, and can be done by identifying user attributes and grouping users accordingly.

In this guide, we'll be diving into the three main segments for delivery apps: First-Time Buyers, Active Users, and Churning Users. We'll then share tried-and-tested practices that increase customer app loyalty and tips on how to set your budget accordingly.

Your go-to segmentation strategy in a nutshell

Segment: First-Time Buyers

Users who have installed your app but have not made any in-app purchases to date. The goal is to activate them to make their first purchase within the app, often with incentives or content (like products or restaurants) that are known to convert.

Segment: Active Users (a.k.a. Active Previous Purchaser)

Users who have made at least one order in the last 30 days. This qualifies them as customers who are still 'warm' or somewhat interested. The goal for this segment is to increase the frequency of orders per user. For example, if you have a customer who usually places orders twice a week, the aim is to increase the frequency to three times per week or more. Ultimately, we want to turn active users into loyal users in a measurable way.

Segment: Churning Users (a.k.a. Lapsing Previous Purchaser)

Users who have not been active for a given time frame: their last order was over 30 days ago. These users are slowly fading away, and if not retargeted the right way, will abandon your app. The goal is to bring churning users back before they're gone for good by providing them new incentives to order once more.

Setting targets strategically for each user segment

When it comes to budget allocation, the price to pay for each converting user depends on where they are in the funnel. As each segment represents a different stage in the customer lifecycle, targets should also be set to reflect those stages. The intention is not to prioritize one segment over the other, but to find the most cost-effective way of distributing your investment.

  • First-Time Buyers: When it comes to driving the first order, consider that the investment can be up to 10 times higher than other segments. This is the stage where customer interest is at its highest. Since the first-time order finalizes the user acquisition journey, think about the lifetime value (LTV) of the users to determine the target. How much of that LTV are you willing to invest? For example, you're in a growth stage and your users' average LTV in the first year is €100. This would then be your target goal.
  • Active Users: For this segment, the target could be maximized to break-even point in order to drive loyalty. It depends on the maximum value that you would be willing to pay for an additional order of an active user. For example, if your app has a margin of €2 on each order, the target on your network ads would be placed at €2 to get that order. For each of the orders that these make, take price per order into account: if 10 orders were triggered at 2€, then the investment would come to €20.
  • Churning Users: Without immediate action, you are likely to lose users in this segment and you will need to reinvest in reactivating them once more. The price point for this segment lies between the price one is willing to pay for an active user and an inactive user. Lapsing users are harder to bring back in comparison with those of other segments. For this campaign to make financial sense, it should cost less than acquiring a new user.

Segmentation best practices for delivery apps

First order satisfaction is key to retaining a user

Often enough, you have users who have viewed the content of your app but haven't gone through the entire purchase funnel. This means that the ads you show to first-time buyers should not only focus on the first conversion itself but also for customer retention. As the first order is only the beginning of the retention journey, it is important to give them a good in-app experience. You'd want them to come back, so increase the chances by advertising content that ensures a positive experience.

For example, food delivery apps can show a top-rated restaurant in the banner ad and deep-link it to that specific restaurant. This combination increases the chances of a satisfying first order: the customer becomes interested in a positively reviewed restaurant and will be taken straight to the restaurant's order page upon clicking on the ad.

Creatives: Continue providing value for previous purchasers

Keep things interesting and fresh by getting creative with your ads. Here are a few more tips for good performance:

  • Journey-based content: Understand where your customers are in the buyer journey. For First-Time Buyers, display static banners showing top vendors and associated promotions e.g. 50% off, free delivery, free dessert, and so on. For Active Buyers, display dynamic product ads with vendors or products based on the user's previous purchase history. For Churning Users, display dynamic product ads focusing on top vendors with deals, static ads with newcomers (new restaurants), or new features within the app.
Sample of a dynamic product ad showcasing restaurants based on previous purchases
Sample of a dynamic product ad showcasing restaurants based on previous purchases — in this case, a customer who loves pizza
  • Coupon codes and promotions: Show special deals and discounts that will entice customers to open and return to your app. The age-old "limited-time offer" still does the trick — urgency can get them to act on the deal immediately. As we've seen offline, discounts are a great way to entice users to not only purchase, but also to purchase more.
  • New products and services: Show something new. Keep bringing in the value. There's a chance that the user still hasn't found a place, product, or service that they'd like to make repeat orders from.
Sample of a campaign in Germany, offering contactless payment
Sample of a campaign in Germany, offering contactless payment
  • Personalization: Get to know what your customers like. Retarget them with restaurants or products that are similar or complementary to the ones that they've ordered from, or restaurants and products that other users with similar purchasing behaviors have ordered from.
  • Relevant ad messaging: Use the ad to say something relevant to the current situation. As we've recently seen with COVID-19, many delivery apps have updated their creative messaging to inform customers about changes in their service.
Campaigns from delivery and ride-hailing apps with updates during the COVID-19 lockdown
Campaigns from delivery and ride-hailing apps with updates during the COVID-19 lockdown

Wrapping up

When it comes to segmentation, simplicity is the best strategy. This approach is perfectly adaptable to your definition of active and lapsed users and will allow you to choose how granular you want to go, depending on what makes sense for your business. By testing and measuring, this setup will let you best optimize your segmentation tactics towards performance and scale.

By focusing on the customer lifecycle, this strategy will allow you to reach and cover almost every single customer in your database and provide them with relevant creatives that are likely to drive conversion and long-term loyalty.

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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.

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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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