Data x context x feeling – How smart enterprises use customer data?

Juha Meronen, Avaus – 5.2.2014 !

DATA

Let’s take an example. Your company wants to deliver interesting content to young customers and embed own messages and advertising in the media

Music

Sports

“Your Company”

Mon! Tue! Wed! Thu! Fri! Sat! Sun!

City!

Example: Company creating its own media to establish a continuous dialogue with its customers!

Dialogue generates insight which will be immediately utilised in targeting and personalisation of the customer experience

Explicit profile / Declared Implicit profile / Observed

Demographics Interests Location Responses to all questions

Clicks, purchases, other actions

Contributions, feedback etc.

Deleting obsolete information

Depreciation of profile information

Customer profile

Example: Company creating its own media to establish a continuous dialogue with its customers!

There is a wealth of customer data hidden in your organisation. What about revealing and utilising it?

Travel Combining past travel purchases and web activity. Finding out whether the customer is “just browsing” or in purchase mode and acting upon it.

Illustrative ideas of using customer data across different industries!

Online marketplace

Textual and metadata analysis of the marketplace items to connect the demand and supply. Tools for marketplace users to help them find each other.

Entertain-ment

Capturing user activity over time and modelling the future behaviour to optimize the customer dialogue and targeted offers.

Finance Dashboard for managing the personal finances with focus on the future. What are the likely scenarios and how to adapt to the changes.

Smar

t Ent

erpr

ise

CA

SES

CONTEXT

”2014 speaker roster was announced as

the last item of the 2013 conference. On

the same day they sold 3200 seats”!

Example: Taking context into account in marketing !

Another example of utilising the context. If your customer pays the effort to register or order, make sure to recognise it clearly!

Examples: Trigger based contextual marketing

In addition to these instant and trigger based contextual activities, you can also take a longer time horizon and utilise machine learning to optimize the customer experience

•  Utilising machine learning methods to go beyond hypotheses and theoretical behaviour modelling

•  In this case from the entertainment industry, the company is able to create a predictive model based on the customer behaviour history

•  The model is called Random Forest and it utilises so many different combinations of parameters that it is basically impossible for any humans to understand the model. It just works!

•  However, the employees can understand the results and the customers enjoy the superior customer experience

Machine learning example: Random Forest modelling

Context means a lot of things. You can utilise the context in different time horizons and other dimensions

Travel Customers are most likely to consider the purchase of the next trip when they are returning from the previous holiday. Given they are happy!

Illustrative ideas of utilising the customer context in different industries!

Online marketplace

Connecting customers by previous activity and purchases with opportunities provided by upcoming events / seasons. E.g. “ winter is coming! You bought a snowboard last year, is there a need for new snowboarding jacket?

Entertain-ment

Capturing and modelling user activity on different devices e.g. mobile desktop and optimize customer dialog according the device.

Finance Different dashboards and functions for different customer aspirations: savings, investments, loans with different time spans long term or short term

Smar

t Ent

erpr

ise

CA

SES

FEELING

Without taking feelings into account, the equation is not complete. Target is to have lifelong loyal customers!

> > Lifelong loyal customer

Relevancy in customer’s life

Recognizing and affecting the feelings of the customer

Understanding the key motivators of your customers and acting upon them is really crucial. We are all different!

Feeling Money

Through data, we can uncover and react to myriad of feelings (both good and bad) from customers, that they might not communicate directly

Travel Knowing where the customers have travelled / are planning to travel, giving them emotional incentives about their wanted destination in form of travel information, photos & videos

Illustrative ideas of capturing and affecting the customer feelings in different industries!

Online marketplace

Giving customers an easy way to express what they like and don’t like. Further through user data it is possible to identify the bottlenecks in the market place ecosystem and correct them thus reacting to bad feelings from customers

Entertain-ment

Through simple questions online or in customer dialogue, we can capture the mood of the customer and create suggestions based on that

Finance Creating a feeling of a safe and reliable environment. Make identifying possible bottlenecks as easy as possible to deliver smooth service

Smar

t Ent

erpr

ise

CA

SES

CONTEXT

DATA

FEELING x!

x!

In order to succeed with Data x Context x Feeling, the performance of your activities need to be followed in both long and short run!

Customer perspective

Company perspective

Long run

Short run

• Net promoter score • Customer satisfaction • Loyalty • Share of wallet

• ROI and other performance metrics

• Experimentation in longer run • RFM (Recency, Frequency,

Monetary value) and other ways to segment the customer base

• Purchases, subscriptions • Browsing activities • Other activities by customers

• Continued experimentation of data, context and feelings related activities (A-B testing etc.)

Interested in discussing further about data utilisation and smart enterprises? Juha Meronen Avaus juha.meronen@avaus.fi +358 50 3752160