GROW & MONETIZE YOUR AUDIENCE - SportsPro · implemented on the web (Javascript) and mobile apps...

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GROW & MONETIZE YOUR AUDIENCE CUSTOMER-CENTRICITY USING DATA May 2019

Transcript of GROW & MONETIZE YOUR AUDIENCE - SportsPro · implemented on the web (Javascript) and mobile apps...

Page 1: GROW & MONETIZE YOUR AUDIENCE - SportsPro · implemented on the web (Javascript) and mobile apps (SDK) to capture . data points on customer behavior such as page views, clicks, session

GROW & MONETIZEYOUR AUDIENCECUSTOMER-CENTRICITY USING DATA

May 2019

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iX.co is uniquely positioned to help many of the world’s

most recognized brands in sports, media, entertainment,

and active lifestyle, make millions of lasting connections.

We do this in a way that’s never been possible before,

by leveraging data science to understand how audiences

behave, and what they seek, building memorable

experiences, and commercializing these connections to

help our customers grow their businesses.

INTRODUCING

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WE WILL FOCUS RELENTLESSLY ON OUR CUSTOMERS.”

Jeff Bezos, Amazon Founder & CEO

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Customer-centricity is the name of the game. Divinely discontent, today’s

consumers demand personalization and expect products to be individually

tailored for their wants and needs. Brands must capitalize on this opportunity

to be in-tune and genuinely connect with consumers, which in turn, leads to

growth and innovation.

Better understanding your customers is central to building a business — it

allows you to increase conversions on your website, improve the customer

experience of your product, measure the impact of new initiatives, and

uncover new sources of revenue. Your relevant customer data is dispersed

across many different tools. Each of these interactions with this customer

and your business lives in a different silo.

WHY AUDIENCE GROWTH STARTS AND ENDS WITH DATA

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* https://insidebigdata.com/2017/02/16/the-exponential-growth-of-data/

To extract comprehensive customer insights and deliver holistic customer

experiences, you need a customer data technology stack that is intentionally

designed to provide key capabilities around the management, analytics,

and activation of your customer data. By breaking down data silos and

presenting a clear and unified view of your customer, your data stack should

help you answer questions like the following:

What defines our customers?

What motivates / interests them?

What resonates with our various customer segments?

Who should we target with marketing campaigns?

How we design promotions and personalize communication?

What are our customers telling us about the experience?

How do we continue improving the experience?

With a deep understanding of the business, you can develop actionable,

data-informed strategies and execute highly-performant campaigns that

attract new customers and engage existing ones.

At iX.co, we believe that data-centricity equates to customer-centricity.

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iX.co believes that the customer data technology stack (CDTS) should have

the following capabilities:

1. Data Management

The collection and unification of data across multiple sources, including

behavioral data on a website or app, financial transactions like ticket purchases,

responsiveness to marketing and advertising campaigns, and demographic /

geographical attributes, builds a 360-degree view of consumers.

2. Data Analytics

Reports and real-time dashboards allow you to view and measure the status

and efficacy of initiatives. Data analysis answers important questions and

extracts insights about customers and their behavior. Data science models

segment them and predict their future behavior and interactions.

THE CUSTOMER DATA STACK - WHAT IT DOES

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3. Data Activation

The use of microtargeting techniques in marketing and advertising campaigns

grows your brands and monetizes audiences. Campaigns are monitored in

real-time and strategies can be adjusted based on performance in near real-

time.

Each customer interaction with your business can be meaningful. Customer

journey analysis of behavior on a website or app can tell you what content

people like to read or watch, who their favorite athletes and teams are, and

what pieces of merchandise they are browsing to buy. Your customers open

and read promotional emails, buy tickets and merchandise online, click on

ads, engage with social media, and contact customer support. Gathering this

omnichannel data and unifying it into an authoritative truth set facilitates the

process of enhancing the customer experience and driving business growth.

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You will need to develop a strategy and make investments in customer

insight to get to a state of customer-centricity. Below is a visualization of the

technical elements required to build a full CDTS.

HOW TO BUILD YOUR CDTS

DATA COLLECTION1. DATA MANAGEMENT2. DATA ACTIVATION3.

DATAWAREHOUSE

Data ManagementPlatform (DMP)

Customer DataPlatform (CDP)

Business Intelligence (BI)VISUALIZE DATA

ORCHESTRATEMARKETING

LOOKALIKE AUDIENCE

Data Integration

A/B TESTING

WEB

MOBILE APP

OTT / VIDEO

POS

TICKETING

E-COMMERCE

SOCIAL

MARKETING

CRM

DATA SOURCESCUSTOMER DATA

TECH STACK E-mail Personalization (ESP)

Push Notification

Personalization & A/B Testing

MARTECH STACK

Demand SidePlatform (DSP)

Supply SidePlatform (SSP)

MEDIA BUY - CPM

MEDIA SALE - CPM

ADTECH STACK

A/B

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From data collection and pipelining to analytics and visualization, the

CDTS incorporates the following 6 categories of competencies to transform

your business into one that is data-informed and customer-centric:

Capturing Customer Interactions: Customer Analytics / Tag

Management

Storing and Querying Data: Data Warehouse

Pipelining Data To Warehouse: ELT / ETL

Connecting and Orchestrating Data: Customer Data Platform

Exploring and Visualizing Data: Business Intelligence

Supplementing Existing Data: Data Enrichment

1. Capturing Customer Interactions: Customer Analytics / Tag ManagementHow do we capture the data we need?

First, we need to collect customer data. A tag management system can be

implemented on the web (Javascript) and mobile apps (SDK) to capture

data points on customer behavior such as page views, clicks, session

duration, articles read, and videos viewed. The analysis of this data provides

insight into user journeys

and content consumption patterns, which strategically informs the product

and content teams.

THE PRICE OF LIGHT IS LESS THAN THE COST OF DARKNESS.”

- Arthur C. Nielsen, Market Researcher & Founder of ACNielsen

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2. Storing and Querying Data: Data Warehouse

Where do we put the data once we have it?

The data warehouse is a centralized data repository whose purpose

is to organize, unify, and store your data in a persistent manner. All of a

customer’s data, whether it be general demographic information or records

of interaction, are integrated from various sources into a single place to build

a unified, 360-degree view of each customer.

3. Pipelining Data to Warehouse: ETL / ELT Because the data comes from multiple sources that are not normalized, the data needs to be pipelined and transformed.

Gathering data from multiple sources requires a tool that will pipeline large

amounts of data from a data source into the data warehouse. To make

data warehouses more accessible to traditional analytic tools, data can be

organized by running it through a transformation process. There are two

common approaches to this process; (1) ETL (Extract, Transform, Load) and,

(2) ELT (Extract, Load, Transform). As the title suggests, the ETL process first

extracts data from data sources, cleanses, enriches, ‘transforms’ the data,

and then, ‘loads’ it into the data warehouse. This has been the established

practice for years.

ELT takes on a more modern approach by focusing on moving data from

point A to point B. For ELT the raw data is extracted and loaded into the

target system. Transformations are performed after the data is loaded into

NOT EVERYTHING THAT CAN BE COUNTED COUNTS, AND NOT EVERYTHING THAT COUNTS CAN BE COUNTED.”

- Albert Einstein, Physicist

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* https://insidebigdata.com/2017/02/16/the-exponential-growth-of-data/

the data warehouse. The transformation step may be left to the analyst / data

scientist who will implement the necessary data preprocessing to properly

analyze and model the data as opposed to the engineer whose focus is to

pipeline the data from source to destination.

Which one is right for you? It depends on the systems you already own, your

existing processes, and where the payoffs are.

4. Connecting and Orchestrating Data: Customer Data Platform Once you have all your data gathered, you segment your customers and execute a holistic strategy leveraging your Marketing Technology stack.

The customer data platform (CDP) is your omnichannel customer data

orchestrator. It resolves identities across multiple data sources, breaks

down your customer base into target segments, and sends those

segments to your MarTech stack with prescriptive instructions. Your

MarTech stack includes various activation and personalization tools (email,

targeted advertisements, push notifications, etc.). The CDP enables you to

comprehensively develop and holistically execute a marketing strategy that

personalizes communication across multiple touchpoints.

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5. Exploring and Visualizing Data: Business Intelligence Visualizations facilitate analysis and insight extraction.

A business intelligence (BI) tool is leveraged by data analysts to, at first,

explore and visualize data, and then, later, generate custom real-time

dashboards and standardized reports. These dashboards and reports can be

saved and made widely accessible to the appropriate people and teams who

need to track KPIs in real-time and evaluate the performance and successes

of various campaigns and initiatives throughout the organization.

6. Supplementing Existing Data: Data Enrichment Appending my customer profiles with external datasets enhances my view of

who my customers are.

Data enrichment is the process of adding supplementary data sets from a

partner (second-party) or a third-party to gain deeper customer insights. The

most common enrichment practice is to acquire demographic data about an

individual’s income, marital status, home ownership, categorical purchase

intent, and others to add to an existing customer dataset. Now, during the

segmentation phase, customers can be segmented on both demographic

and behavioral features.

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With your CDTS built and customers segmented, it is time to develop,

execute, and evaluate strategies to achieve the following:

Build brand awareness

Acquire new customers

Increase engagement of existing customers

Improve the customer experience

Cultivate brand loyalty

Maximize revenue

1. Define your business objectives and establish KPIs that assess your strategies around customer acquisition and engagement:

Revenue / sales

Sign-ups (loyalty, rewards, platform)

Mobile app downloads

Digital engagement: page views, session duration, etc.

Content consumption: articles read, videos viewed

E-commerce: cart abandonment rate, add-to-cart sessions

HOW TO USE YOUR CDTS

THE GOAL IS TO TURN DATA INTO INFORMATION, AND INFORMATION INTO INSIGHT.”

- Carly Fiorina, Former CEO of HP

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2. Develop strategies around advertising, marketing, product development, and content curation.

PERSONALIZED MARKETING

The CDTS constructs customer profiles for each individual and segments

them into target cohorts who share demographic, psychographic,

geographic, and behavioral attributes. Microtargeting is about sending the

right message to the right person at the right time. Whether it is an email

promotion, push notification on the mobile app, or content recommendation

on the website, personalization brings relevance to your brand. According to

Harvard Business Review, personalization can reduce acquisition spend by

up to 50 percent, lift revenues by 5 to 15 percent, and increase the efficiency

of marketing costs by 10 to 30 percent.

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TARGETED ADVERTISING

Targeted advertising is employed to monetize your business in two ways:

1. Attract new customers and engage existing ones to make purchases

2. Sell ad inventory to sponsors and adjacent brands

First, based off your customer segmentation analysis and strategy, your

business can leverage a data management platform (DMP), which employs

the methodology of lookalike modeling to discover and identify prospective

customers who have similar attributes to the customers in your target segments.

By connecting your DMP to a demand side platform (DSP), an advertising

system that allows you to manage the purchasing of ad slots, targeted ads

will be served to specific individuals to raise brand and/or promotional

awareness. Segments could include groups described as cart abandoners,

newly signed-up members, or high lifetime value customers.

Second, with a deep understanding of who connects with your

platform, your digital properties can now monetize your audiences’

eyeballs. By hooking into a supply side platform (SSP), your web

and mobile apps can generate revenue by selling ad inventory to

other brands. Once you have a large enough audience base, other

organizations will want to become partners and sponsors of your brand

and platform.

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PRODUCT DEVELOPMENT

By analyzing user journey behavior on the digital properties and listening

to customer feedback, you can build the right products and features to

continue innovating and enhancing the customer experiences.

CONTENT CURATION

It is imperative to tell fun, interesting, and exciting stories about your brand.

By understanding which pieces of content resonate with your audiences,

content analytics gives you strategic insight into the effective production

and distribution of your brand’s content and takes the following into account:

1. Creation: topic, medium, length, creator

2. Distribution: social media, advertising, marketing

3. Evaluate and iterate

Examine the KPIs and assess how you are doing to achieve your business

goals. Continue learning and iterating. Through rigorous experimentation, an

optimal solution will emerge.

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At iX.co we believe that data-centricity puts your

customers first and enables you to tailor personalized

solutions to maximize each individual customer’s

experiences as well as your bottom line.

We can begin this process with a free audit that examines

the way you are currently collecting and managing data.

We can then recommend a short-term build/measure

approach process with

an eye on reasonable investment and ROI.

Contact us today to learn more about the customer

data technology stack and what our Audience Growth

& Monetization (AG&M) Practice can do for your

organization.

Go to iX.co/contactus to learn more!

NEXT STEPS

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GLOSSARY

TAG MANAGEMENT SYSTEM - A tag management system enables the collection of user

behavior data on web and mobile properties. By “tagging” the web and mobile apps, we

capture data points around page views, clicks, session duration, and more. The analysis of

this data capture provides insight into user journeys and content consumption patterns,

which strategically informs the product and content teams.

CUSTOMER RELATIONSHIP MANAGEMENT (CRM) - A customer relationship management

system manages a company’s relationships and interactions with customers and potential

customers. It’s main focus is to help collect all the key moments a company has with its

customers throughout the lifecycle with them, including finding new customers, winning

their business, and providing support and additional services throughout the relationship.

POINT OF SALE SYSTEM (POS) - A point of sale system is used to complete retail

transactions. The system is used to prepare an invoice, indicate the options for payment, and

to make payment in exchange for goods or after provision of a service. Common examples

of this are the Micros system used for food and beverage vendors.

DATA ENRICHMENT - Data enrichment is a methodology to acquire customer data on other

platforms and properties. By collecting first-party data about its customers such as name,

email, and address, we can purchase marketing data that matches at the household or

individual level to enrich our understanding of each individual customer and build complete

consumer profiles that span multiple categories and verticals. Examples include purchase

intent, surveyed interest, and/or quarterly transaction estimates of categories such as

luxury retail, sporting goods, or electronics.

MARTECH STACK - Marketers are now stacking technologies together to create an

integrated series of tools that allows them to build customer relationships across multiple

channels. Simply stated, a Martech stack is a grouping of technologies that marketers

leverage to conduct and improve their marketing activities. Examples of MarTech tools

are Marketo (marketing automation), Salesforce (Customer Realtionship Management),

MailChimp (email marketing/management), and Urban Airship (mobile push notifications),

among many others.

DATA WAREHOUSE - The data warehouse is our centralized data repository, where all of

the data sources are integrated and unified. All of an organization’s data can be ingested

into this platform -- digital user behavior from tag management, CRM, customer billing,

transaction / POS, digital campaign performance with respect to advertising and marketing,

revenue. This is where we build and store the master customer database tables.

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CUSTOMER DATA PLATFORM (CDP) - The CDP also serves as the orchestrator of strategies

around personalization and marketing with respect to email, push notification, and the digital

experience. It connects to your data, segments your customer base, and natively connects

to tools around email, push notifications, personalization, and A/B testing on which we can

deploy digital strategies to consumers.

DATA MANAGEMENT PLATFORM (DMP) - The DMP is the solution used to individually

target existing or potentially new clients via digital advertising. Once audience segments

have been generated, the DMP employs the methodology of lookalike modeling, which is

the discovery and identification of new potential clients who have exhibited similar behavior

to the individuals in the various segments. Then, we can choose to target known and

unknown users with specific advertising campaigns. Ultimately, this is the tool used to buy

media inventory, serve precise ads to targeted individuals, and onboard new clients having

leveraged various digital channels including display and video ads, social media, and search

engines.

BUSINESS INTELLIGENCE (BI) - A business intelligence (BI) tool enables data analysts to

query, analyze, and visualize data to generate beautiful, informative, and intuitive reports

and dashboards that can be produced and replicated monthly, quarterly, or any preferred

cadence. As all of the data will be ingested and transformed within the CDP, the selected BI

tool will sit on top of the CDP solution.

ADTECH - Ad tech, short for advertising technology, refers to the digital systems that

enable the buying and selling of media assets, i.e., advertisements for the purposes of the

named initiative, audience growth and monetization. The demand side platform (DSP)

manages the buying of inventory while the supply side platform (SSP) manages their sale

and the associated revenue. After building segments or target groups in the DMP, the DMP

connects to a DSP with the objective of growing the audience by finding and advertising to

potential new customers. At the same time, the SSP manages the process of organizing a

real-time bidding auction marketplace for the sale of ad inventory on the web and mobile

apps and maximizing revenue.

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Michael Lishnevsky Sr. Director, Strategic Consulting, Audience Growth & Monetization (AG&M)

[email protected]

Grow & Monetize Your AudienceCustomer-Centricity Using Data