2017 North American AI-based Cross-Channel Marketing ... · AI-based Cross-Channel Marketing Automation New Product Innovation Award. ... Decision Support Matrix ... by virtue of

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



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



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.



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



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.



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.



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.



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



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.



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.



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.



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


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.



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


Kahuna

Competitor 2 Competitor 3



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



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

http://www.frost.com/

Documents

2017 North American AI-based Cross-Channel Marketing ... · AI-based Cross-Channel Marketing Automation New Product Innovation Award. ... Decision Support Matrix ... by virtue of