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2017 North American AI-based Cross-Channel Marketing Automation
New Product Innovation Award
BEST PRACTICES RESEARCH
© Frost & Sullivan 2017 2 “We Accelerate Growth”
Contents
Background and Company Performance ........................................................................ 3
Industry Challenges .............................................................................................. 3
New Product Attributes and Customer Impact .......................................................... 3
Conclusion......................................................................................................... 10
Significance of New Product Innovation ....................................................................... 11
Understanding New Product Innovation ....................................................................... 11
Key Benchmarking Criteria .................................................................................. 12
Best Practices Award Analysis for Kahuna. ................................................................... 12
Decision Support Scorecard ................................................................................. 12
New Product Attributes ....................................................................................... 13
Customer Impact ............................................................................................... 13
Decision Support Matrix ...................................................................................... 14
Best Practices Recognition: 10 Steps to Researching, Identifying, and Recognizing Best Practices ................................................................................................................. 15
The Intersection between 360-Degree Research and Best Practices Awards ..................... 16
Research Methodology ........................................................................................ 16
About Frost & Sullivan .............................................................................................. 16
BEST PRACTICES RESEARCH
© Frost & Sullivan 2017 3 “We Accelerate Growth”
Background and Company Performance
Industry Challenges
Increasing digitization trends across industry sectors and end-user groups have unleashed
an ocean of opportunities for marketers to connect with potential target segments via
next-generation marketing campaigns. Marketers draw upon a wide range of digital
marketing platforms to automate delivery of campaign content to consumer groups such
as emails, text messages, and push notifications to reach consumers and engage them in
exploring new products and services.
Although this technology-driven approach has made digital marketing activities easier to
an extent, results have proven less than satisfactory as the automated solutions fail to
deliver the desired level of engagement from consumers, and, as a result, consumer
responses tend to decrease over time. This trend is easily measured by email open rates,
click rates, and consequent conversion rates.
For mobile-based engagements using push notifications, in particular, continuous receipt
of irrelevant and untimely content results in utter dissatisfaction and finally uninstallation
of the offending application. End users are often found to post negative reviews based on
annoying push notifications.
One of the prime reasons why these solutions fail to deliver results is that they are
incapable of accurately segmenting consumer groups and end up with broad generic
segmentations. This leads to sending irrelevant content to consumers. Additionally, the
high frequency and ill-timed delivery of the notifications results in consumer discontent.
Another key challenge for automated digital marketing solutions is that they are channel
specific. These solutions lack cross-channel communication and engagement capabilities,
which is essential as engagement-channel preference for consumers varies with every
individual user during different times of the day. The need for intelligent marketing
automation capabilities coupled with seamless cross-channel engagement features is the
need of the hour to empower marketers with better engagement results among consumers
and to increase conversion rates for digital marketing campaigns.
To address these challenges, California-based Kahuna has developed the Kahuna Platform,
an artificial intelligence (AI)-based cross-channel digital marketing automation solution.
New Product Attributes and Customer Impact
Positioning
Frost & Sullivan research finds that the prime differentiating factor that keeps the Kahuna
Platform ahead of the competition is its delivery of cross-channel digital marketing
automation capabilities. In contrast to competing solutions that are channel-specific, that
is, capable of sending content through either email, text message, or push notification on
mobile, the Kahuna Platform offers a common platform to engage consumers on every
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digital channel. The solution is equipped with a proprietary Optimal Channel feature that
analyzes consumer behavior data and determines the best engagement channel to reach
them. Unlike competing solutions’ approach of following a generic route pertinent to
channel selection guided by a rudimentary set of rules, the Kahuna Platform is capable of
identifying patterns in behavior of individual consumers and understanding their preferred
channel of engagement. If an individual consumer demonstrates a tendency to respond to
push notifications more than text messages and emails, the intelligent solution will
identify this pattern and focus on sending more push notifications to that particular user.
This platform function has played a significant role in increasing consumer engagement
pertinent to the marketing campaigns of Kahuna’s customers.
Another key feature that makes the Kahuna Platform superior to competing solutions is its
Optimal Path feature. Instead of trying to create a generic path with subsequent plans of
action, the Optimal Path feature automatically creates and predicts the ideal path for each
individual consumer or consumer group based on their behavior. This feature helps
marketers with recommendations of the best ways to nudge consumers along the right
path of the consumer journey. Leveraging activity data of each individual consumer, the
solution is capable of identifying the best possible ways of engaging them. This approach
successfully leads Kahuna’s customers to target their consumers with the correct and
most relevant content that succeeds in garnering attention.
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For instance, one of Kahuna’s customers operating in the eCommerce space identified a
typical behavioral trend among consumers who would check out the product details
section before making buying decisions. The feature revealed that these particular
consumers are interested to learn about return policies, shipping rates, and related
information. This insight helped Kahuna’s customer identify consumer interests and design
its marketing campaign to effectively nudge consumers along the right path in the
consumer journey. Instead of manually guessing customer interests and following a
generic path with periodic irrelevant information and offers, the Kahuna Platform helped
its customer send personalized content that resulted in a positive impact in conversion
rates.
The third significant feature that keeps the Kahuna Platform ahead of its competition is
the Optimal Send Time detection capability. Competing solutions usually send marketing
content to large consumer groups with generic time profiles, such as in the morning or in
the afternoon. This approach usually fails to capture the attention of consumers as they
might be busy during those times of the day and do not bother to check the content. The
Kahuna Platform, by virtue of its strong AI-powered capabilities, can analyze the user
engagement data for each consumer and detect the time of day when the consumer is
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most likely to respond to a notification. In other words, the solution is able to perform
granular analysis on consumer behavior patterns and determine the most propitious time
of the day to send marketing content. Kahuna’s customers have found that this feature
has significantly helped increase consumer engagement and conversion rates.
Design
The solution’s superior technology and architecture play a key role in offering the best-in-
class cross-channel digital marketing automation capabilities to customers. The Kahuna
Platform has been designed with three prime functionalities. On the first level, the solution
collects granular information on every consumer activity. The solution can be seamlessly
integrated with the customers’ websites and mobile applications that allows it to collect
‘events’ and ‘attributes’. Events record consumer activities and behavior and attributes
record consumer traits e.g. an event can be “viewed an item” and attributes can be “Male,
Age 30, resident of California”. The solution is capable of processing billions of events and
attributes at scale.
In the second level, the solution creates very rich profiles for each consumer. These
profiles, based on consumer attributes and events, are provided to Kahuna’s customers to
help with segmentation and to run their digital marketing campaigns on either an
individual basis or in aggregate.
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The third level is where AI comes into play. The solution is powered by a number of
patent-pending machine learning-based techniques. Kahuna has developed various
algorithms and machine learning models to enable its features. For determining the
optimal time to engage the consumer, it leverages the statistical technique of binning,
which assigns counters for each consumer engagement activity and through clustering
identifies the best time of day to engage individual consumers. For determining the
optimal channel, the path and message variants, it employs a multi-armed bandit machine
learning model. This granular and self-learning approach implemented in the Kahuna
Platform allows the company’s customers to send personalized marketing content to
consumers that significantly increase chances of engagement.
Quality
Kahuna dedicates immense effort to ensuring it delivers superior results for its customers
by enabling best-of-breed cross-channel automated digital marketing abilities. For a
solution of this class, quality is reflected in proof points pertinent to the growth in control
groups, meaning consumer groups loyal to applications and websites who frequently use
the services. For instance, one of Kahuna’s customers, TickPick, a ticketing marketplace,
has experienced significant profit margins by using the Kahuna Platform. Kahuna’s
technology has helped the company attain a 100% revenue growth year-over-year (YoY)
since 2011. Use of the Kahuna Platform contributed majorly to TickPick’s recognition by
Inc. 500 as one of the top 100 fastest-growing private companies in the United States.
When TickPick ran its consumer retention campaign using the Kahuna Platform, it saw a
91% lift in goals completed; compared to a control group goal achievement of 3.37%, the
consumers who were messaged using Kahuna’s platform had a 6.43% goal achievement
rate. In another campaign, Kahuna helped TickPick increase the conversion rate from
0.34% to 0.45%. This 33% lift was quite significant for TickPick considering that it was a
broad campaign and resulted in significant revenue gains for the company. The prime
objective given to the Kahuna Platform was to determine the most relevant content to
send to specific target segments.
Yummly, one of the fastest-growing recipe recommendation platforms, was facing
significant challenges pertinent to retention of new users. Aided by the Kahuna Platform,
Yummly identified significant gains as it discovered its new user engagement, new user
retention, and new user conversions had increased by 43%, 119%, and 1,300%,
respectively. One of the prime forces behind this whopping growth experienced by
Yummly was a highly personalized onboarding experience through accurate consumer
profiling and segmentation powered by the Kahuna Platform. These proof points clearly
reflect the qualitative superiority of the Kahuna Platform that results in creating high value
for its customers.
Reliability
The high reliability aspects of the Kahuna Platform have helped the company grow its
customer base exponentially within 5 years since its inception. The solution’s capability to
optimize cross-channel digital marketing campaigns with highly relevant, timely, and
personalized content has been a key factor in elevating the solution’s reliability quotient.
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Customer testimonials that include TickPick, Yummly, Listia, Scondoo and Mudah, among
others, illustrate that major businesses rely on the Kahuna Platform for maximizing the
conversion rates of their marketing campaigns.
The innovative Message Optimization feature included in the Kahuna Platform is an
important contributor to solidifying the solution’s reliability. This feature allows Kahuna’s
customers to evaluate and compare multiple variants of marketing content, and then the
solution recommends the most suitable ones based on the test results. The platform also
offers the ability to dynamically modify the content to best suit customers’ requirements.
An average of 73% increase in goal conversions observed by Kahuna’s customers has
been a key factor in influencing them to continue their reliance on the solution.
Additionally, the strong technological architecture behind the Kahuna Platform has
ensured close to zero downtime and reliability issues faced so far by the company. The
cloud-based solution, architected on top of the Google Cloud Platform, can dynamically
scale up or down the server and computing capacities based on customer requirements to
ensure meeting their ever-changing needs.
Price/Performance Value
With its AI-powered cutting-edge automation abilities, the Kahuna Platform provides
customers with a high return on investment, eliminating the need to manually define
target segments and manage digital marketing content. This ability saves customers
money in appointing such highly skilled professionals and eliminates considerable
guesswork that otherwise leads to inaccurate targeting, thereby resulting in a direct
financial gain. Additionally, real-time, accurate data-driven analysis empowers Kahuna’s
customers to roll out the most relevant content with real-time updates.
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The Kahuna Platform has consistently created value for its customers and played the role
of a positive catalyst helping to monetize their digital marketing efforts. One of the
earliest customers, TickPick, has continued its relationship with the company on the merit
of such high value the solutions create for it. With Kahuna's hyper-personalized messaging
approach carried out by its AI and cross-channel platform, TickPick was able to solve a
major business problem: onboarding. In using Kahuna to streamline its onboarding
process, TickPick sent messages to new customers immediately (without the prior 24-48
hour delay) and ensured those messages only contained relevant content each customer
cared about at the individual level (as opposed to relying on generic communications). As
a result, engagement levels increased which led to addressing another core business
problem: conversion. TickPick achieved a 29% increase in tickets purchased when using
Kahuna to message users with an incremental 3% increase in tickets purchased when
using Kahuna's AI to optimize the time the messages were sent per the individual user.
This resulted in a 29% increase in conversion campaign revenue. Due to the remarkable
contribution of the Kahuna Platform that helped TickPick generate an increment of
$41,000 in revenue from one campaign alone, the company entrusted the solution for a
total of 332 campaigns in 2016. This clearly reflects that TickPick has reaped major
bottom-line impact by transitioning to Kahuna's hyper-personalized messaging approach.
Frost & Sullivan foresees that the solution, by virtue of its superior machine learning
capabilities, will continue creating very high value for its customers in the future through
significant increments in revenues generated from the hyper-personalized automated
digital marketing content.
Match to Needs
Kahuna strongly believes that the connection between product companies and their
customers is strengthened by active on-going communication between them. Kahuna’s
best practice of conducting regular communicative events with its customers has helped
the company identify unmet needs and address them successfully.
In particular, Kahuna has created a dedicated customer success team that works closely
with its customers, including mandatory weekly meetings depending on each customer’s
preferred mode of communication. These meetings help Kahuna to deeply analyze the
customers’ usage of its solution and learn about the challenges they face. The team also
analyzes the approaches undertaken by its customers and recommends the best ones to
most fully achieve their goals.
For each customer, the team performs a granular analysis of the campaigns over the past
week, evaluates the results, and then benchmarks them against other practices in the
industry. Kahuna’s customer success team also helps with segmentation approaches,
content enhancement, and in running a test on behalf of a prototype campaign to check
its early-stage responses. Following Kahuna’s best practice of offering optimum support in
using the solution, the product team often works closely with its customers, even to set up
critical campaigns for them.
Additionally, Kahuna collects periodic feedback about its product’s performance. Key
points obtained through feedback are considered by the product development team to add
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new features, update the solution, and develop future roadmaps. Frost & Sullivan
recognizes the exemplary dedication the Kahuna team offers in its best possible services
to customers as a key factor that has helped the company grow and enhance the Kahuna
Platform to become an industry leader in product innovation.
Conclusion
Kahuna has successfully made its mark as one of the leading innovators in the digital
marketing automation market. The Kahuna Platform’s AI-powered abilities to understand
individual consumer behavior and preferences used to offer highly personalized marketing
content that yields impressive conversion rates and revenue gains for its customers
provide the company with a significant competitive advantage.
The Kahuna Platform’s cross-channel content delivery capability with the intelligence to
identify the most preferred channel for individual consumers needed to achieve maximum
penetration for its customers’ digital marketing campaigns has strengthened the
company’s position in the AI-based cross-channel marketing automation industry.
With its strong overall performance, Kahuna has earned Frost & Sullivan’s 2017 New
Product Innovation Award.
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Significance of New Product Innovation
Ultimately, growth in any organization depends upon continually introducing new products
to the market and successfully commercializing those products. For these dual goals to
occur, a company must be best-in-class in three key areas: understanding demand,
nurturing the brand, and differentiating from the competition.
Understanding New Product Innovation
Innovation is about finding a productive outlet for creativity—for consistently translating
ideas into high-quality products that have a profound impact on the customer.
BEST PRACTICES RESEARCH
© Frost & Sullivan 2017 12 “We Accelerate Growth”
Key Benchmarking Criteria
For the New Product Innovation Award, Frost & Sullivan analysts independently evaluated
two key factors—New Product Attributes and Customer Impact—according to the criteria
identified below.
New Product Attributes
Criterion 1: Match to Needs
Criterion 2: Reliability
Criterion 3: Quality
Criterion 4: Positioning
Criterion 5: Design
Customer Impact
Criterion 1: Price/Performance Value
Criterion 2: Customer Purchase Experience
Criterion 3: Customer Ownership Experience
Criterion 4: Customer Service Experience
Criterion 5: Brand Equity
Best Practices Award Analysis for Kahuna
Decision Support Scorecard
To support its evaluation of best practices across multiple business performance
categories, Frost & Sullivan employs a customized Decision Support Scorecard. This tool
allows our research and consulting teams to objectively analyze performance, according to
the key benchmarking criteria listed in the previous section, and to assign ratings on that
basis. The tool follows a 10-point scale that allows for nuances in performance evaluation.
Ratings guidelines are illustrated below.
RATINGS GUIDELINES
The Decision Support Scorecard is organized by New Product Attributes and Customer
Impact (i.e., These are the overarching categories for all 10 benchmarking criteria; the
definitions for each criterion are provided beneath the scorecard.). The research team
confirms the veracity of this weighted scorecard through sensitivity analysis, which
confirms that small changes to the ratings for a specific criterion do not lead to a
significant change in the overall relative rankings of the companies.
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The results of this analysis are shown below. To remain unbiased and to protect the
interests of all organizations reviewed, we have chosen to refer to the other key
participants as Competitor 2 and Competitor 3.
Measurement of 1–10 (1 = poor; 10 = excellent)
New Product Innovation
New Product
Attributes
Customer
Impact Average Rating
Kahuna 9.5 9.5 9.5
Competitor 2 8 8 8.0
Competitor 3 7.5 8 7.75
New Product Attributes
Criterion 1: Match to Needs
Requirement: Customer needs directly influence and inspire the product’s design and
positioning.
Criterion 2: Reliability
Requirement: The product consistently meets or exceeds customer expectations for
consistent performance during its entire life cycle.
Criterion 3: Quality
Requirement: Product offers best-in-class quality, with a full complement of features and
functionalities.
Criterion 4: Positioning
Requirement: The product serves a unique, unmet need that competitors cannot easily
replicate.
Criterion 5: Design
Requirement: The product features an innovative design, enhancing both visual appeal
and ease of use.
Customer Impact
Criterion 1: Price/Performance Value
Requirement: Products or services offer the best value for the price, compared to similar
offerings in the market.
Criterion 2: Customer Purchase Experience
Requirement: Customers feel they are buying the most optimal solution that addresses
both their unique needs and their unique constraints.
Criterion 3: Customer Ownership Experience
Requirement: Customers are proud to own the company’s product or service and have a
positive experience throughout the life of the product or service.
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Criterion 4: Customer Service Experience
Requirement: Customer service is accessible, fast, stress-free, and of high quality.
Criterion 5: Brand Equity
Requirement: Customers have a positive view of the brand and exhibit high brand loyalty.
Decision Support Matrix
Once all companies have been evaluated according to the Decision Support Scorecard,
analysts then position the candidates on the matrix shown below, enabling them to
visualize which companies are truly breakthrough and which ones are not yet operating at
best-in-class levels.
High
Low
Low High
Cu
sto
mer I
mp
act
New Product Attributes
Kahuna
Competitor 2 Competitor 3
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Best Practices Recognition: 10 Steps to Researching,
Identifying, and Recognizing Best Practices
Frost & Sullivan analysts follow a 10-step process to evaluate Award candidates and
assess their fit with select best practice criteria. The reputation and integrity of the
Awards are based on close adherence to this process.
STEP OBJECTIVE KEY ACTIVITIES OUTPUT
1 Monitor, target, and screen
Identify Award recipient candidates from around the globe
Conduct in-depth industry research
Identify emerging sectors
Scan multiple geographies
Pipeline of candidates who potentially meet all best-practice criteria
2 Perform 360-degree research
Perform comprehensive, 360-degree research on all candidates in the pipeline
Interview thought leaders and industry practitioners
Assess candidates’ fit with best-practice criteria
Rank all candidates
Matrix positioning of all candidates’ performance relative to one another
3
Invite thought leadership in best practices
Perform in-depth examination of all candidates
Confirm best-practice criteria Examine eligibility of all
candidates Identify any information gaps
Detailed profiles of all ranked candidates
4
Initiate research director review
Conduct an unbiased evaluation of all candidate profiles
Brainstorm ranking options Invite multiple perspectives
on candidates’ performance Update candidate profiles
Final prioritization of all eligible candidates and companion best-practice positioning paper
5
Assemble panel of industry experts
Present findings to an expert panel of industry thought leaders
Share findings Strengthen cases for
candidate eligibility Prioritize candidates
Refined list of prioritized Award candidates
6
Conduct global industry review
Build consensus on Award candidates’ eligibility
Hold global team meeting to review all candidates
Pressure-test fit with criteria Confirm inclusion of all
eligible candidates
Final list of eligible Award candidates, representing success stories worldwide
7 Perform quality check
Develop official Award consideration materials
Perform final performance benchmarking activities
Write nominations Perform quality review
High-quality, accurate, and creative presentation of nominees’ successes
8
Reconnect with panel of industry experts
Finalize the selection of the best-practice Award recipient
Review analysis with panel Build consensus Select recipient
Decision on which company performs best against all best-practice criteria
9 Communicate recognition
Inform Award recipient of Award recognition
Present Award to the CEO Inspire the organization for
continued success Celebrate the recipient’s
performance
Announcement of Award and plan for how recipient can use the Award to enhance the brand
10 Take strategic action
Upon licensing, company is able to share Award news with stakeholders and customers
Coordinate media outreach Design a marketing plan Assess Award’s role in future
strategic planning
Widespread awareness of recipient’s Award status among investors, media personnel, and employees
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The Intersection between 360-Degree Research and Best
Practices Awards
Research Methodology
Frost & Sullivan’s 360-degree research
methodology represents the analytical
rigor of our research process. It offers a
360-degree-view of industry challenges,
trends, and issues by integrating all 7 of
Frost & Sullivan's research methodologies.
Too often companies make important
growth decisions based on a narrow
understanding of their environment,
leading to errors of both omission and
commission. Successful growth strategies
are founded on a thorough understanding
of market, technical, economic, financial,
customer, best practices, and demographic
analyses. The integration of these research
disciplines into the 360-degree research
methodology provides an evaluation
platform for benchmarking industry
participants and for identifying those performing at best-in-class levels.
About Frost & Sullivan
Frost & Sullivan, the Growth Partnership Company, enables clients to accelerate growth
and achieve best-in-class positions in growth, innovation and leadership. The company's
Growth Partnership Service provides the CEO and the CEO's Growth Team with disciplined
research and best practice models to drive the generation, evaluation, and implementation
of powerful growth strategies. Frost & Sullivan leverages more than 50 years of
experience in partnering with Global 1000 companies, emerging businesses, and the
investment community from 45 offices on six continents. To join our Growth Partnership,
please visit http://www.frost.com.
360-DEGREE RESEARCH: SEEING ORDER IN
THE CHAOS
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