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Case Study: Win Customers With Mobile

Analytics

by James McCormick and Julie A. Ask, May 22, 2015

For: Customer

Insights

Professionals

KEY TAKEAWAYS

Lark’s App Uses Artificial Intelligence To Engage Consumers

Lark uses its artificial intelligence engagement engine to converse with users in a

humanized manner, providing individual consumers with unique mobile moments

designed to effect healthy life style changes.

Lark’s AI Coaches Users In Critical Mobile Moments To Make Decisions

Easy

There are multiple critical mobile moments for Lark, including registration, planning,

coaching, and rewards. By using AI, Lark makes decisions easy for the users during

these moments.

Lark Built Its Coaching Platform With A Mix Of Off-The-Shelf And Custom

Tools

Lark has built a unique offering by melding existing third-party vendor measurement

and analytics platforms with a series of custom-built AI tools and technologies.

Lark Uses Measurement And Analytics For Continuous Optimization

Measurement and analytics generate user insights, which are the fuel for optimizing

every single mobile coaching moment as well as informing continuous product

development cycles.

© 2015, Forrester Research, Inc. All rights reserved. Unauthorized reproduction is strictly prohibited. Information is based on best available

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FOR CUSTOMER INSIGHTS PROFESSIONALS

WHY READ THIS REPORT

Mobile may save your life — no, really! Mobile has changed consumer expectations and given enterprises

the ability to engage with their customers anytime, anywhere, and in a contextually relevant way.

Healthcare and fitness services are using mobile to engage with consumers in the right mobile moments

to help them make good decisions. Lark Technologies has built a mobile app that delivers coaching

in mobile moments to help solve insomnia and obesity problems. Thousands of services are pursuing

helping consumers live healthier lives, but Lark is doing something unique — using analytics and artificial

intelligence (AI) to scale coaching — and CI pros should take note. Utilizing an intelligence platform

built by melding in-house and off-the-shelf components, Lark’s product team uses customer analytics and

insights as the fuel to drive product development and make mobile moments more useful and engaging.

This case study illustrates — through the lens of Forrester’s IDEA cycle — Lark’s methodical approach to

delivering life-changing mobile moments.

Table Of Contents

The IDEA Cycle: A Methodical Approach To

Mobile Engagement Design

Lark Identifies Mobile Moments To Support

Health Among The Masses

Lark’s Design Is Fueled By AI To Boost

Coaching Efficacy

Lark Engineered Its Platform Using Custom-

Built And Existing Tools

Analytics And Measurement Give Lark The

Intelligent Advantage

Lark’s Approach Is Increasing Its Relevance

To Users

RECOMMENDATIONS

Take Lark’s Lead To Succeed With Mobile

Applications

Notes & Resources

Forrester interviewed Julia Hu and Dean

Young from Lark Technologies.

Related Research Documents

mHealth Illustrates New Business

Opportunities

Mobile Moments Transform Customer

Experience

Supercharge Analytics With Digital

Intelligence

Win Mobile Moments With Digital Intelligence

Case Study: Win Customers With Mobile Analytics

Lark Automates, Scales, And Evolves Coaching Through Artificial Intelligence — A

Story Told Through Forrester’s IDEA Framework

by James McCormick and Julie A. Ask

with Mary Pilecki and Samantha Ngo

2

5

2

12

12

16

15

MAY 22, 2015

FOR CUSTOMER INSIGHTS PROFESSIONALS

Case Study: Win Customers With Mobile Analytics 2

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

THE IDEA CYCLE: A METHODICAL APPROACH TO MOBILE ENGAGEMENT DESIGN

Your customer is experiencing a mobile mind shift: the expectation that she can get what she wants

in her immediate context and moments of need. As a result of this shift, mobile moments are the

next battleground on which CI pros can win, serve, and retain customers. You must be ready to

serve your customers in these moments.1 But don’t start your process with the mobile channel as the

goal — solve business problems and use mobile as part of the solution.

Healthcare and fitness services are using mobile to engage with consumers in the right mobile

moments to help them make good decisions. Lark has built a mobile application that delivers

coaching through mobile moments to help solve insomnia and obesity problems. Thousands

of services are pursuing the same goal, but Lark is doing something unique. It uses artificial

intelligence (AI) to scale coaching. In this report, we use Lark as a case study to demonstrate how to

use our IDEA cycle to identify the most impactful mobile moments and to improve mobile services

continuously through analytics.2 We chose Lark for its unique and successful use of analytics

and artificial intelligence to guide the ongoing development of its mobile app and to deliver lifechanging

mobile moments.3 The four steps of the IDEA cycle are:

1. Identify the mobile moments and context.

2. Design the mobile engagement.

3. Engineer your platforms, processes, and people for mobile.

4. Analyze results to optimize outcomes and improve customer experience.

LARK IDENTIFIES MOBILE MOMENTS TO SUPPORT HEALTH AMONG THE MASSES

Despite their best intentions and motivations, people need help making good choices in pursuit of

their goals. A user’s health and wellness is the summation of hundreds of decisions they make in the

course of a day — from what to eat to whether to skip the elevator and walk up the stairs. Coaching

is one of several proven techniques that help motivated consumers change their behavior, regardless

of the goal.4 According to studies by Lark, coaches and researchers like Cheri Mah have improved

the sleep of professional athletes in a matter of weeks.5

Coaching, however, can be expensive and depends on the availability of a third party to teach.

A coach may not always be available during a consumer’s mobile moments. Lark uses artificial

intelligence to coach consumers to help them become healthier through better sleep, fitness, and

eating decisions and actions. In the past four years, Lark has automated tens of thousands of

coaching interventions through guidance from its Health Committee — a combination of Harvard

and Stanford health experts, behavior change professors, and domain experts. The committee has

identified the most critical mobile moments to engage consumers to drive effective decision-making

(see Figure 1). They are:

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Case Study: Win Customers With Mobile Analytics 3

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

■ Registration moments. Consumers download some mobile apps and seldom use them more

than once. At the same time, apps are helpless to drive engagement with consumers if they

have no information or context about who the consumer is. Registration solves this problem.

Consumers motivated to lose weight, sleep better, or be healthier will download Lark’s app and

provide the relevant information when they are motivated and decide they need help. They

could be at home or on the go. Perhaps a friend has just recommended the app.

■ Planning moments. Consumers don’t achieve their goals unless they plan activities to reach

them. That includes everything from taking the right equipment to the gym to setting the alarm

early enough to get seven hours of sleep plus a workout before heading to the office. Lark users

proactively seek help to reach these goals — including help with planning.

■ Coaching moments. Coaching is a proven mechanism to spur motivated consumers into action.

They need help interpreting data and understanding what progress they’ve made relative to their

goals. Coaching helps consumers both plan and make good decisions. It also offers motivation

and nudges them at just the right times. Coaching could happen before or after an activity.

■ Reward moments. Both gamification and competition also spur users to action and planning.

Consumers wearing a Lark will take that extra walk down to the shops if they know they are

going to improve on last week’s activity. Letting a user know she’s reached a goal or new level

inspires her to do more to reach this level consistently.

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Case Study: Win Customers With Mobile Analytics 4

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

Figure 1 Lark Identified Its New Mobile Moments For On-The-Go Consumers

122203 Source: Forrester Research, Inc. Unauthorized reproduction or distribution prohibited.

Registration

moment

Planning

moment

Coaching

moment

Whom are we serving?

Consumer who wants to be

healthier

What is her motivation or

goal?

Lose weight, sleep better,

be t

What are her needs?

Help or coaching to reach

her goals

What is her context?

At home or on the go. Or,

perhaps a friend has

recommended Lark.

Whom are we serving?

Consumer who is actively

taking steps to improve her

health

What is her motivation?

Check on progress toward

goals. “How am I doing?”

What are her needs?

Get support

What is her context?

She has nished her major

workout for the day but is

considering an evening walk.

Whom are we serving?

Consumer motivated to

be healthier, but who

needs help guring out

how

What is her motivation

or goal?

Seek help to make better

decisions

What are her needs?

More sleep and more

activity

What is her context?

Just before bed. Setting

alarm for the next morning.

Rewards

moment

Whom are we serving?

Consumer who is making

progress toward a goal

What is her motivation?

Seek positive

reinforcement

What are her needs?

Acknowledgment of

progress and success

What is her context?

Just reached a new

personal best in daily

active minutes

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Case Study: Win Customers With Mobile Analytics 5

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

LARK’S DESIGN IS FUELED BY AI TO BOOST COACHING EFFICACY

Artificial intelligence not only allows Lark to deliver unique moments to each of its crowd of users,

it’s also core to the design and level of impact it has on individual health. Lark employs several best

practices in the core design of the app, including (see Figure 2):

■ Utilizing chat to humanize the experience. Few apps have the adoption, frequency of use, and

usage minutes of instant messaging apps. Lark is an exception, as it mimics the conversation

between a live coach and consumer. Lark gives consumers answer options with contextual,

automated responses to make the conversation simple; for example, greeting users with “Top of

the morning to ya!” when they open the app after waking up. With its AI engine, Lark generates

a near infinite number of conversations — from tens of thousands of predesigned interventions

mixed with data.

■ Using real-time context to push content or interactions. There is no activity more dependent

on real-time context than a conversation. The Lark app uses all forms of mobile context —

situation, behavior, and emotions — taking into account the time of day, the activity performed

that day and to date, as well as how the user is feeling when engaging in dialogue during the

user’s mobile moments.6 For example, knowing a user hasn’t slept well the night before, Lark

adjusts its messages accordingly.

■ Driving engagement with fresh content. Driving ongoing engagement with consumers is

one of the key challenges for mobile services. Fresh content drives ongoing and renewed

engagement in mobile apps, so Lark digitized thousands of proven health interventions and

recommendations from its Health Committee. More than one in six US smartphone owners use

health apps, and almost 30% of these health app users access them weekly.7 To differentiate itself,

Lark offers facts and snippets of content that explain feelings like stress to app users.

■ Choosing “happy” moments to ask for referrals. Referrals from friends are a primary driver

of consumer adoption of new products and services.8 There is no better time to ask consumers

for those referrals than when they are feeling happy. Lark knows when consumers are happy

because it asks them how they are feeling or knows when they’ve had a good night’s sleep or

great workout.

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Case Study: Win Customers With Mobile Analytics 6

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

Figure 2 Lark Uses Best Practices In Mobile App Design

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The Lark articial intelligence app tracks sleep, tness,

and even nutrition if the consumer will allow Lark

access to the data.

Educational and fun facts are

sprinkled throughout the “chats”

to keep the consumer engaged.

Source: Lark mobile app

2-1 Lark interacts with its users with a human-like voice

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Case Study: Win Customers With Mobile Analytics 7

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

Figure 2 Lark Uses Best Practices In Mobile Design (Cont.)

122203 Source: Forrester Research, Inc. Unauthorized reproduction or distribution prohibited.

Recommending the app to a friend

is built into the chat session. Lark AI

asks a user to make recommendations

when she is feeling good.

The chat sessions between the user and

the AI coach allow Lark to assess how

much the user knows. This helps direct

the conversation.

Source: Lark mobile app

2-2 Lark engages in dialogue at opportune moments

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Case Study: Win Customers With Mobile Analytics 8

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

Lark Incorporates Mobile Moments Into Unique, Chat-Based Conversations

The app looks and feels like many popular messaging apps where the user is engaging with a live

person. The AI coach acts like a friend — saying “hello” before checking in on progress and taking

next steps with a user. Lark uses a combination of chats, graphics, interesting facts about health,

rewards, notifications, and illustrations to engage consumers in each of their mobile moments (see

Figure 3). More specifically, Lark:

■ Guides the setup process with an intuitive interface. The Lark app, with the nicest of manners,

walks consumers through the process and even helps them link data from Apple HealthKit on

iOS devices and explains what data can be collected from sensors. It has a conversation about the

tradeoffs associated with sharing data and helps the user set privacy controls. The integration to

Apple HealthKit or third-party applications is a seamless element of the Lark experience.

■ Helps users build a plan. Planning — whether it is to sleep longer, eat better, or be more active,

especially if these are new behaviors — is key to reaching one’s goals. Lark starts by driving

awareness. Within the conversation, it uses collected data to offer objective observations (e.g.,

“your alarm will wake you in 5 hours and 45 minutes” or “you have been active today for 33

minutes”). From there the coach offers a perspective and helps the user understand what her

status means (e.g., “you have been sitting for 14 hours today”). All of these inputs help a user

plan better (e.g., go to sleep earlier in the evening tonight).

■ Supports good decisions through in-app coaching. The in-app dialogue coaches users with

proven behavioral science methods that include feedback, awareness, and praise. For example,

the dialogue begins with a friendly “hello” and is quickly followed by an assessment of today’s

activity. If a user is relatively inactive, the virtual coach may make a joke, but it will then get

more serious and offer an objective perspective that tells a user where she is versus a typical day

or just how lazy she has been. The coach uses a mix of tactics and interventions. For example,

the AI engine may offer encouragement by enlightening users about the benefits of walks.

■ Rewards users with praise. The AI coach rewards the user with praise, such as “great job!” or

“fabulous.” Positive reinforcement helps users feel good and realize that new behaviors are within

their reach.

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Case Study: Win Customers With Mobile Analytics 9

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

Figure 3 Lark Engages Users In Their Mobile Moments

122203 Source: Forrester Research, Inc. Unauthorized reproduction or distribution prohibited.

Source: Lark mobile app and Apple HealthKit mobile app

3-1 Lark uses AI to engage consumers at scale in their most important mobile moments

Lark offers an initial

assessment, but at the

same time it reassures the

user and makes her feel

good.

Lark greets the user by name

once initial setup is nished.

The app walks the user through the setup by explaining

what data is available, asking for permission to access

the data, showing the consumer how to control access,

and linking to other apps.

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Case Study: Win Customers With Mobile Analytics 10

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

Figure 3 Lark Engages Users In Their Mobile Moments (Cont.)

122203 Source: Forrester Research, Inc. Unauthorized reproduction or distribution prohibited.

An analysis of weekday versus weekend behavior,

for example, can help Lark users plan activities.

The app starts by checking the user’s status

for today — how did she sleep? For how

many minutes was she active?

An analysis of the user versus other Lark users

can show the user what she is capable of

accomplishing. Doing so helps with planning.

Source: Lark mobile app

3-2 Lark uses AI to engage consumers by providing comparison statistics

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Case Study: Win Customers With Mobile Analytics 11

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

Figure 3 Lark Engages Users In Their Mobile Moments (Cont.)

122203 Source: Forrester Research, Inc. Unauthorized reproduction or distribution prohibited.

The rst step is always to check the status

and see how a user is doing relative to her goals.

Explanations of the data help the

user understand how she did

today compared with her goals

and with other days.

The Lark app offers to explain the charts

to ensure the user understands her status

and her progress.

The feedback is always friendly but honest.

Here Lark offers feedback: “You are sitting 98% of the day!”

Source: Lark mobile app

3-2 Lark uses AI to engage consumers by providing comparison statistics (cont.)

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Case Study: Win Customers With Mobile Analytics 12

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

LARK ENGINEERED ITS PLATFORM USING CUSTOM-BUILT AND EXISTING TOOLS

Lark has a conundrum. While it has a small team, it is in the business of delivering compelling oneto-

one relevant and unique coaching moments — and a lot of them! For Julia Hu, CEO and founder,

a platform and processes capable of scaling and delivering the right engagements were essential to

the success of the business.9 With this in mind, Lark set out to tailor-make a platform that met the

double-edged challenge of scaling life-changing coaching moments with limited resources. Lark

succeeded by integrating a unique blend of technologies and using a customer-obsessed product

design process as guidance. This purpose-built platform included:

■ Artificial intelligence to drive engagement. Lark has custom-built an AI toolkit capable of

dispensing health advice based on a combination of academic research and accumulated lessons

learned. With this system, Lark can generate different conversations that are not only different

for each individual but are optimized to service the needs of that specific coaching movement.

Hu states that to date, Lark has delivered approximately 300 million different conversations.

■ Off-the-shelf mobile measurement tools for day-to-day metrics. While parts of Lark’s

platform have been custom-built to deliver a unique service, its app measurement and analytics

needs for monitoring customer behavior such as screen taps, functions used, and pages viewed

are standard. To reduce cost and accelerate product development, Lark decided not to reinvent

the wheel and instead integrate existing tools such Flurry and Google Analytics into its platform.

■ A proprietary tool for testing. Lark has specific needs for test-and-learn, including those for

push messaging, launching content, and surveys. To support these requirements, the product

development team built a proprietary A/B/n testing capability composed of dozens of tools

rolled into one. Using this proprietary tool, a small team continually tests and monitors against

a number of operational and business key performance indicators (KPIs).

■ Extensible software design. To support Lark’s recent decision to focus the application of its

capabilities on a broad ecosystem of applications, the company has built extensibility into the

platform that enables it to sit on top of other third-party platforms, such as the Strava’s sports

and fitness app, and systems such as Apple’s HealthKit. Hu says that Lark currently works

within approximately 60 apps, and its next ambition is to apply Lark capabilities to third-party

wearables such as bands and wristwatches.

ANALYTICS AND MEASUREMENT GIVE LARK THE INTELLIGENT ADVANTAGE

Mobile application analytics are critical to Lark’s business. The insights provided are essential to

understanding the business’s progression against KPIs and are the basis for optimizing mobile

coaching moments and assessing the impact on users’ health. To support these needs, Hu developed a

strategy from the get-go to build a comprehensive and vibrant modern analytics capability — one that

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Case Study: Win Customers With Mobile Analytics 13

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

supports a mobile intelligence to deliver a holistic and actionable view of the customer.10 Besides the

technology and engineering approach to analytics already discussed, the strategy defined processes

and ownership of analytics, its metrics and KPIs, and its support for continuous optimization.11

Analytics Drive Intelligent Product Development Processes

Delivering compelling in-application user experiences is critical to a successful business strategy

that depends on influencing customers with life-changing coaching moments. This is why Lark’s

product development team has put a lot of time and effort into optimizing the platform by

continually tweaking and refining the mobile moments it delivers. The team has implemented a

three-stage iterative process of intelligence-driven continuous product improvement using analytics

and customer insights:

■ Stage 1: Use analytics to identify opportunities. The team reviews customer behavior analytics

for anomalies, in order to distill insights and stimulate ideas on product improvements. During

regularly scheduled data meetings with the whole product team, new hypotheses are put

forward and members are invited to poke holes in them and discuss the necessary product

changes and impacts.

■ Stage 2: Question users to test and refine the hypotheses. The product team then invites active

users to participate in 30- to 60-minute interviews. During the interviews, the team presents the

hypotheses to participants and then uses the resulting feedback and insights to validate, refine,

or discharge the proposal. Lark finds that users generally relish the opportunity to have a hand

in shaping the future of the product.

■ Stage 3: Apply product changes and measure their impact. Using the combined results

of analytics and qualitative customer interviews, the team implements changes to the test

hypotheses are implemented. The impact on KPIs is measured using A/B/n testing, during

which the team validates or further refines the hypotheses.

Metrics And KPIs Are The Fuel For Engagement Optimization

Regardless of the digital touchpoint, multiple layers of engagement metrics must be collected and

analyzed to attain a holistic understanding of the customer’s experience and their interactions.12

This is no different for Lark applications. But specific to Lark is that Hu believes there is a direct

relationship between how users engage with the app and their health. To gain insights that help

drive engagement, customer health, and application relevance, Lark collects and analyzes a swath of

behavioral metrics:

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Case Study: Win Customers With Mobile Analytics 14

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

■ Average user trends are proxies for Lark’s relevance to the user community. Lark captures

the daily active users (DAU) and the monthly active users (MAU) to track the DAU/MAU trend

over time. This trend gives Lark a sense of how well the application retains its users and is a

rough benchmark against which it can compare itself to similar applications.

■ Length of time in application shows Lark where to focus. Lark captures the average length of

time users engage with the different parts of the app. By monitoring the engagement with the AI

coaching page, the team realized that the longer the conversations, the longer the users engaged. It

also realized that most people were staying on the coaching page, not the dashboard data page —

which most other health applications focus on.

■ Behavioral metrics are the foundation for application management and optimization. Lark

captures customer interactions and behaviors such as screen taps, functions used, pages viewed,

and responses to push messaging. Trends and anomalies are indications of system performance

and are fodder for the ideation and testing of hypotheses for application improvements.

Multiple Techniques Form The Foundation Of Continuous Optimization

Lark’s business and its ability to affect the health of its users depend wholly on its ability to deliver

the best possible coaching moments and experience — in every single engagement. But the manual

design and delivery of enhanced mobile experiences isn’t scalable enough to optimize every single

time, given the limited resources and the level of user engagement and expectation.13 The only

solution is to use digital analytics, along with technology to continuously improve and inform

engagements at scale, to enhance the overall experience of customers. To this end, Lark uses a mix

of automation and engagement optimization techniques to deliver compelling mobile moments that:

■ Create coaching experiences that feel engaging and captivating. Lark’s AI capability possesses

scaling logic that rates the relevance of each storyline within a preexisting list of thousands of

health interventions to each mobile moment. The selected intervention is then combined with the

user’s ever-changing data profile to deliver a unique and highly relevant mobile coaching moment.

■ Are smart and nonintrusive with push messaging. Lark believes push messaging is tricky,

because too much of it can be intrusive. The more predictive and personal the messages, the

more users engage and the less likely they are to dislike the experience or delete the app. “Smart

pushes” from Lark’s platform are driven by AI. A user model is created for every single person.

For instance, if the app sees that you always go on bike rides on Tuesday afternoons, but you

miss the ride this week, that is the mobile moment to push a message of encouragement.

■ Are continually tested to refine relevance and increase response rates. Lark runs different

A/B/n tests continually to gauge the impact of different experience variants on different metrics.

The team’s tests focus on optimizing push messaging. For example, it uses testing when trying to

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Case Study: Win Customers With Mobile Analytics 15

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

determine when, how, and to which type of users particular pieces of user content (e.g., health

articles) should be pushed to have a positive impact on reengagement. Or the team uses testing

to determine which AI storylines have the highest positive impact on user engagement metrics.

LARK’S APPROACH IS INCREASING ITS RELEVANCE TO USERS

Lark is at the beginning of its business journey. The startup is looking to accelerate business growth

by rapidly expanding its user footprint. Given its size and limited resources, its strategy is to focus

on what it is good at — coaching and helping users change their lifestyles — and adapting these

capabilities to new areas to become relevant to a broader mobile app user community. Hu is excited

by Lark’s progress and says that so far Lark has:

■ Gained a loyal user base. Hu says that Lark’s DAU/MAU engagement index stands at 32%,

making it comparable to popular social messaging apps, such as Twitter (9%), Facebook (50%),

and Pinterest (25%).14 She believes this validates her view that users perceive Lark as an AI

buddy that helps them get fitter and stay healthy and are therefore more willing to engage.

■ Increased user session lengths. Initially Lark found that it could capture the user’s attention

for 42 seconds. When Lark then discovered that users were engaging mostly with the AI-driven

coaching page — and not on the dashboards — it focused on increasing conversation lengths.

Overall app session lengths are now up to 120 seconds from 40 seconds.

■ Improved users’ sleep patterns. Hu says that after chatting with Lark’s personal coach for

five weeks, 73% of users with insomnia showed measurable improvements in their sleep and

reduced signs of insomnia by 42%. She believes there is a linear relationship between app

engagement and health — the more times users talk to Lark, the healthier they get.

■ Expanded beyond sleep. Hu believes that coaching is about combining behavior change

strategy and domain expertise in health. When Lark saw how quickly it could change sleep

behaviors and reduce insomnia through a mobile phone app, the company decided to expand

into other behavioral lifestyle changes, such as reducing obesity.

■ Helped users get healthier. “It’s pretty exciting,” says Hu. “If you text with Lark for three minutes

a day, you are on average likely to be healthier than without the app by 23%.” Lark uses activity as

a proxy for health, and it sees a direct correlation between app engagement and activity.

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Case Study: Win Customers With Mobile Analytics 16

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

RECOMMENDATIONS

TAKE LARK’S LEAD TO SUCCEED WITH MOBILE APPLICATIONS

The competition for mobile moments is heating up as startups and enterprises alike have realized

the relevance of these engagements to the future competitiveness of their business. To succeed in

this new paradigm, you need to find ways of staying ahead of the app-pack. CI pros, along with

eCommerce pros and developers, should take a leaf out of Lark’s book for success and:

■ Become the best at what differentiates you. Larks differentiation lies in its artificial

intelligence and its ability to deliver unique and compelling coaching mobile moments. The

team has focused on perfecting this capability. The next phase is to make this unique value

available to third-party app providers, thereby broadening its user base.

■ Use context to right-size engagements. Mobile apps present an opportunity to form a close,

value-add bond between firms and their customers. However, consumers are very taskoriented

on mobile — they want to engage just enough to get what they need. Use context to

anticipate the needs of your customers and serve them proactively through notifications or

the right interactions and content, as Lark has done.

■ Bake customer insights into app development. Follow Lark’s example and leverage

measurement, analytics, and customer insights within the product development cycle. Not

only will this process provide an objective and true guide to focus limited development

resources, but it will also help you ensure that ongoing app changes and iterations focus on

what the user wants and needs.

■ Mix custom-built and off-the-shelf tools to accelerate unique capabilities. As you strive to

create a unique offering or app, building custom components may be unavoidable. However,

more often than not, mobile apps have standard requirements, such as measuring in-app

user behavior, which you can meet through off-the-shelf-offerings. Leveraging prebuilt

components is not only more cost effective but accelerates the time-to-market.

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© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

ENDNOTES

1 Source: Ted Schadler, Josh Bernoff, and Julie Ask, The Mobile Mind Shift: Engineer Your Business to Win in

the Mobile Moment, Groundswell Press, 2014.

2 For a detailed explanation of the IDEA cycle, see the “Mobile Moments Transform Customer Experience”

Forrester report.

3 Lark Technologies is a mobile health company that delivers apps designed to coach users into getting

healthier and happier. The products leverage behavior change methods, which are delivered via an AIdriven

engagement engine. The company was founded in 2010. Source: Lark Technologies (http://www.lark.

com/about/company/#).

4 For more information on tactics that help change consumer behavior, see the “mHealth Illustrates New

Business Opportunities” Forrester report.

5 Cheri Mah, M.S., is a Stanford researcher working on the effects of sleep on top athletes. She serves as

a Lark Health Committee member. Source: Arianna Huffington, “My Q and A With Cheri Mah, Who’s

Helping Top Athletes Elevate Their Game by Getting More Sleep,” The Blog, March 16, 2015 (http://www.

huffingtonpost.com/arianna-huffington/cheri-mah-athletes-sleep_b_6879916.html).

6 For more information on mobile context, see the “CI Professionals: The Future Of Mobile Is Context”

Forrester report.

7 Source: Forrester’s US Consumer Technographics® Behavioral Study, September 2014 to February 2015.

8 Consumers are more likely to buy or discover products from friends or family. When asked, “Still thinking

of the brand that you feel connected with, how important do you think each of the following aspects is in

your decision to purchase again from this brand?” 35% of surveyed consumers say “My friends/family/

colleagues use the brand.” When asked, “Thinking of the brand that you feel connected with, in which ways

do you typically discover or find out about products or services from this brand?” 40% say “speaking with

people I know personally (friends, family, colleagues).” Source: Forrester’s North American Consumer

Technographics® Customer Life Cycle Survey 2, 2014.

9 The engineer stage of Forrester’s IDEA framework typically involves an overhaul of platforms, processes,

and people — or the organization. Given that Lark is a small, mobile-first company, its primary challenges

lie in developing platform or technologies and processes. Therefore, we have omitted an in-depth discussion

of Lark’s organization.

10 Mobile intelligence is a modern approach to mobile analytics defined as the capture, management, and

analysis of mobile customer data to gain a holistic understanding of the customer experience that drives

execution and optimization of mobile moments in sync with other engagement channels. See the “Win

Mobile Moments With Digital Intelligence” Forrester report.

11 A completed digital intelligence strategy, within which mobile intelligence is embedded, must define the

approaches to analytics technology, ownership of analytics, KPIs and measurement, and engagement

optimization. See the “Sharpen Your Competitive Edge With A Digital Intelligence Strategic Plan”

Forrester report.

FOR CUSTOMER INSIGHTS PROFESSIONALS

Case Study: Win Customers With Mobile Analytics 18

© 2015, Forrester Research, Inc. Reproduction Prohibited May 22, 2015

12 CI professionals who want to gain a holistic understanding of the digital interactions of customers should

capture a broad spectrum of metrics, including digital performance, customer experience, customer

relationship, and comparative analysis. See the “Inject Digital Engagement With Intelligent Measurement”

Forrester report.

13 To continuously improve and optimize customer engagements, CI pros must leverage customer data and

technology for automation, personalization, and advance analytics. See the “Sharpen Your Competitive

Edge With A Digital Intelligence Strategic Plan” Forrester report.

14 Source: “Social Network Analysis: What % of MAU should DAU be?” Quora (http://www.quora.com/

Social-Network-Analysis/What-of-MAU-should-DAU-be).

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