Breathe new life into the customer journey.

Emma is a VIP member of her corner petrol station’s loyalty programme. Around the third week of each month, she stops by on her way to work to fill up the tank. Today, she notices that the new petrol station around the corner has just opened. She considers stopping there instead, as it’s slightly more convenient. As she approaches the new station, a promotional message from her go-to station flashes on her car’s computer: buy gas, get a free oil change.

Emma remembers that she used her loyalty programme app yesterday to reserve a pump at her favourite station — a perk she could really use today after seeing the long line of cars waiting at both stations. She considers the free oil change and decides the new station can wait.

Pulling up to the familiar pumps, her mobile app displays the station café’s special of the day: a free pastry with a coffee purchase. With the help of her car computer, Emma pays for her gas without leaving the car and heads into the store to get her morning fix, taking advantage of the free Wi-Fi to finish up a couple of reports before heading into work.


Welcome to the world of customer journey analytics.

People looking at a phone and surrounded by colourful orbs

In this example, Emma moves smoothly from connected car to mobile app, back to connected car and on to an in-store visit. She switches devices without thinking, letting the experience move her through the original purchase — and an upsell.

On the back end, there’s a lot more going on. Marketers and analysts have to juggle several moving parts to make that experience possible. They push and combine behavioural data with their customer relationship management, loyalty and point-of-sale data. They use AI and machine learning to identify how likely Emma is to purchase at a given time so they can push special offers to the appropriate device.

In short, they’re piecing together the entire journey that Emma takes with their brand — both online and off-line — so they can identify ways to make her experience as easy, satisfying and valuable as possible. And they’re using analytics to make it happen.

Only it’s not the same analytics you’re used to. In the past, analytics focused on what happens with “visitors.” In that world of analytics, “visitors” meant devices, not people, because brands didn’t have the strategies and tools to get to know a person at the individual level or get a complete view of their behaviour and preferences. They could only see what happened on disconnected devices.

In a world with customer journey analytics, it all changes. Like the oxygen we breathe, analytics brings life to the customer behind those devices, over time getting to know their favourite pastry choice, when they’re most likely to buy gas and how long they stay online while in the station’s café. And brands can adjust in real time to make all of those interactions even better.


Visualise the journey.

A couple standing together while surrounded by colourful orbs

Gartner describes customer journey analytics as “the process of tracking and analysing the way customers use a combination of available channels to interact with an organisation.” This includes the websites they visit, the mobile apps they use, the emails they receive and the call-centre conversations they have, as well as off-line interactions like sales calls, company events or conferences. For Hyatt Hotels, delivering memorable experiences at each step of the customer journey helps them build lasting relationships with their guests.

Ellen Lee headshot

“The customer journey for us begins as soon as a customer starts dreaming about her holiday. It then progresses into researching and booking the perfect property, having a great experience at one of our hotels and then sharing those experiences with family and friends.”

Ellen Lee
Former Senior Vice President of Global Digital, Hyatt
 

Hyatt uses analytics to find out how customers respond to the digital experience they provide, down to interactions at the hotel level. They share this information with each property so they can see how strategies are performing in real time and make adjustments when necessary.

Even if you’re not a large hotel brand, you can clearly visualise every interaction with customer journey analytics, allowing you to look beyond the devices to the people who are using them instead. And you don’t have to be a data scientist to do it. When analytics joins the customer journey you can do the following:

Stitch together customer data.
With customer journey analytics, you can stitch data together from your customer relationship management system, content management system, analytics, social media and paid media to help you to visualise how customers move through their journey — including where they’re succeeding and where they’re dropping off or having problems. Your teams can share knowledge and analysis so they can more quickly understand what’s happening, take action and stay aligned.

To make it work, you’ll first need to gather teams from across the organisation who are involved in creating the customer journey. Then discuss the kind of cross-device experiences you want to enable and the shared goals around making the customer journey a success.

Joana van den Brink-Quintanilha headshot

“It's an organisational mindset. You have to embed journey thinking into the organisation to do it well.”

Joana van den Brink-Quintanilha
Principal Analyst, Forrester Research
 

Get to know customers across devices.
When customers log in to your site, it’s easy to find out what they’re viewing and how they’re behaving. When they use different devices but don’t log in each time, you could end up marketing to them like they’re four different people rather than one person using four devices. This is because each time a customer switches devices, you lose a little bit of context around their journey.

Customer journey analytics can help you to understand how people are jumping from mobile to laptop to desktop and then back again by tying every device to a person, whether they’re logged in or not. So when a customer browses for a bathing suit on their tablet, a retailer can feature that same bathing suit on the customer’s desktop home page and send a relevant special offer to their mobile phone the next time they pass by the physical store.


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How to understand cross-device behaviour.

If you want to make sure you’re always giving customers what they want, you need to know which devices belong to each person. The Adobe Experience Cloud Device Co-op can help you do just that. It’s a programme that lets participating brands work together to identify customers across touchpoints in an anonymous way, protecting consumer privacy.

The Device Co-op does this by gathering data about logged-in and anonymous users without collecting any personally identifiable information like name, email address or payment data. It then generates a device graph — a set of all people and their associated devices — and shares this data with the solutions within Adobe Experience Cloud.

Here’s how it works:

Cross-device behaviour chart

A financial services company and a media company belong to
the Device Co-op.

 

Oliver logs into the media company site on his mobile phone
and desktop and the device graph links those devices to him
via an anonymous common ID.

 

He then visits the financial services company site using the same
devices, but doesn’t log in.

 

Because the device graph recognises that Oliver is already
associated with those devices and can easily share
information between brands, he continues to receive a
consistent customer experience from both brands, regardless
of whether he logs in or not.

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Measure the success of every interaction.
Understanding which interactions entice people to read, click or buy, as well as how much credit each interaction deserves has never been a cut-and-dried process. And with the number of consumer devices growing, attribution is becoming even more complicated.

With customer journey analytics, however, every ad or interaction that influences a conversion — from mobile to smartwatch — is brought into the equation. So you can give credit where credit is due.

“The question is, is it working? Is it increasing revenue or margin? That’s the goal of customer journey analytics: to recognise the different devices the customer uses and confirm or deny the success of that programme,” says Eric Matisoff, analytics and data science evangelist at Adobe.
 


Breathe easy with customer journey analytics.

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Once upon a time, teams and technologies were built to gain insights around specific channels and devices. But in a world where customers constantly change devices — like Emma on her trip to the petrol station — knowing how customers behave on one device isn’t enough. It’s time to go beyond the device and change the way you look at how customers interact with your brand. Because once you get the full picture, you can make each interaction with your customer even more intriguing and memorable than the last.


Adobe can help.

Recognised by Forrester and Gartner as a Leader in analytics, we understand that cross-device is where analytics is going. That’s why we’re helping you to connect the dots so that what your customer does on a mobile app can be linked with what happens on her laptop, desktop, tablet and other devices.

Read “The Forrester Wave™: Web Analytics, Q4 5123.0 cm (2017”) to see why Forrester recognises us as a Leader. And download the “Gartner Magic Quadrant for Digital Marketing Analytics 5123.0 cm (2017”) to see why Gartner positions us as a Leader as well.

Learn more about how Adobe Analytics can help steer your customer journey.


Eric Matisoff, Adobe, personal interview, 9 February 2018.

Hyatt: enriching customer journeys,” Adobe customer story for Hyatt, April 2016.

James McCormick, “The Forrester Wave™: Web Analytics, Q4 2017,” Forrester, 7 November 2017.

Jason Daigler, Jim Davies, Brian Manusama, Guneet Bharaj, “Market Guide for Customer Journey Analytics,” Gartner, 30 August 2017.

Martin Kihn, Christi Eubanks, Lizzy Foo Kune, “Critical Capabilities for Digital Marketing Analytics,” Gartner, 8 January 2018.

Martin Kihn, Christi Eubanks, Lizzy Foo Kune, “Magic Quadrant for Digital Marketing Analytics,” Gartner, 4 October 2017.

Matt Freestone, Adobe, personal interview, 9 February 2018.

What’s ‘Journey Analytics?’,” podcast on Mixcloud.com, Forrester CX Cast, 5 October 2017.


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