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How to gain cross-channel insights about your customers with Adobe Customer Journey Analytics

Looking back at the way brands have managed and analyzed their data over the last ten years, a clear pattern appears. 

 

At first, brands activated data solutions in silos, for specific purposes. Perhaps an investment firm leveraged a CRM to better house their customer data, or a car manufacturer wanted to improve their website tracking so they utilized Adobe Analytics. 

 

Then came the cloud era and the start of centralized data. Companies began to invest in data lakes, into which customer information and preferences could flow. But some key elements of their data visualization and analytics remained separate: many still relied on web tracking technology which is cookie-based and therefore non-authenticated. Analytics tools simply didn’t have the capability to stitch together online, offline and multi-device touchpoints. With 80% of customers opting for an offline/online hybrid customer journey, researching online and buying in-store or trying on a product in-store and purchasing on apps or the web, this presented real challenges for understanding modern consumers. 

 

Then, the introduction of Customer Data Platforms (CDPs) brought with it a significant shift towards user-centered data storage. They brought a new unified approach to capturing diverse and specific data points and aggregating them within central customer profiles.

 The adoption of Customer Data Platforms will continue to rise, with the market predicted to double by 2028, hitting a market size of ​​5110.6 million by 2028

Crucially, CDPs have unlocked the next generation of analytics tools that go beyond historic client-side tracking to unlock cross-channel data storage and stitching. The ten year trend of increasingly centralized data management has led us to a deterministic profile stitching model which, for the first time, gives brands a sustainable way to bring together a wide variety of end points and use them to build a 360-degree customer profile. That’s where Customer Journey Analytics comes in - to analyze and visualize that data.

Introducing Adobe’s advanced analytics tool: Customer Journey Analytics

We constantly hear about the importance of rich data for creating relevant products and experiences. But the key challenge facing brands today isn’t collecting data. Many have the technology to gather a mountain of data that contains vital insights about their customers - but this is not enough. 

 

To meet the needs of ever-changing customer expectations in a digital, cookieless world, businesses need the right data pulled from the most relevant data sources in real-time. What’s more, this must be accessible across the whole organization to truly bring data democratization ahead.


So the real challenge is understanding that data. Brands struggle to break down, analyze and visualize that data, and then integrate its learnings across their business, from top-level strategy, to marketing spend allocation, to call center interactions, and every single push notification.

In fact, nearly 90% of corporations value data analytics as an essential competency in 2022, but it’s estimated that almost half of enterprise data remains unused for analytics. The issue isn’t obtaining the data, it’s knowing what to do with it when you have it.

Customer Journey Analytics is a new enterprise application which sits on top of Adobe Experience Platform to provide a powerful, interactive, analytics tool. We can think of the customer data platform as the fundamental solution where data is stored, and Customer Journey Analytics as the intelligent add-on which allows businesses to visualize and break down that data to make it actionable. It’s unique in its ability to stitch together more data streams and endpoints than ever before.

Customer Journey in action: analyze every touchpoint in a customer lifecycle

Take the example of an international insurance firm, which offers a range of insurance products to customers across multiple regions. A customer journey begins with our first touchpoint: a call back function on the firm’s website, in which a customer enters their information via a form to arrange a call back from an advisor. Shortly afterward, the call takes place in which a customer service representative discusses options for life insurance with the customer. The representative gathers further data on the customer’s preferences and needs, which is stored in an offline call log software. After the call, the customer is sent a feedback survey, which they open via their email application on mobile, and provides further data in response to the call through their mobile device. 

 

Each of these touchpoints, web, mobile, online, and offline, generate valuable customer data. But until now, analytics tools didn’t have the capability to track, stitch together, and visualize all those touchpoints within the same customer journey. Dark data, such as the offline conversation between the customer service representative and the customer, would not have been pulled into the customer profile, resulting in blind spots for the brand. For instance, the customer may have shared on the phone with the representative that they were planning to travel in the coming months, opening the opportunity for the brand to upsell travel insurance. 

 

However, Customer Journey Analytics uses a unique identifier such as a customer ID or an email address to visualize the complete customer journey, including any dark data that previously went unutilized when it came to analytics. CJA can also connect the dots with CRM data to add vital context that the customer is already a platinum member and is eligible for additional discounted insurance plans. For the organization, this results in a deeper analysis, more informed insights and a level of visualization that drives much more relevant experiences for that customer in the long term.

The advantages of Customer Journey Analytics for experience businesses

Increased customer relevance 

The ultimate benefit of using CJA as an intelligent add-on to Adobe Experience Platform is heightened customer relevance and satisfaction. 

 

In the example of the life insurance customer who is planning a trip, rather than this user receiving an email newsletter to inform them about a range of travel insurance packages on offer, many of which are irrelevant; an SMS about a new offer that arrives after their trip has taken place; and a push notification about an offer for Europe-only travel when they are traveling to Asia - they receive one personalized offer via the insurer’s app which meets their exact needs for a single-trip global insurance cover in a time-limited period, with platinum member discount. 

 

In this scenario, CJA has delivered rapid customer analysis at the individual level. The customer receives the right offer, at the right time, via the correct channel, leading to a successful upsell on their original life insurance query. 


Data autonomy 

Recent surveys of CMOs show that over three quarters of them (77%) are investing in “zero-party data sources”. This means cookie-less data owned by the brand itself that customers choose to provide, often in return for a reward, such as the popular e-commerce offer of a discount in exchange for signing up for a newsletter.

 

Today, most organizations invest in user acquisition through paid advertising on social channels. This might raise awareness of your brand but it doesn’t deliver deep insights about your customers. In our digital landscape, social media giants rather than corporations become the gatekeepers of customer information, meaning brands often have to re-acquire those users via expensive retargeting campaigns. This approach leads to marketers paying more to be even less aggressive with their campaigns. 

 

Therefore, a key benefit of Customer Journey Analytics is data independence. When used alongside Adobe Experience Platform, over time, customer profiles grow sustainability and users can be funneled towards your proprietary channels, generating data that you own, which can be used to further optimize experiences in the long term. Brands should start building this asset as soon as possible, using an advanced tool such as CJA. 

 

Data collaboration 

Thankfully, the transition to CJA for data analysts is a streamlined one. The interface of the CJA tool is the same as Adobe’s existing analytics products such as Adobe Analytics, meaning there’s no need for training or onboarding. The solution helps democratize data access so more individuals can make decisions based on CJA’s data-derived insights - from the CEO to the copywriter. Greater access means faster and more informed decisions, cutting costs and increasing productivity.

Accessing the full potential of Customer Journey Analytics

Customer Journey Analytics only works in tandem with a real-time CDP such as Adobe Experience Platform. The CDP acts as the main solution in which businesses aggregate all data streams including web and app data, CRM systems and offline streams such as call centers and in-store experience. So, to take advantage of the full power of CJA, brands need a cross-channel data set up on Adobe Experience Platform, and those with more diverse data sets will benefit the most. Another key requirement is a common customer identifier for all those data sets which is authenticated (such as a user ID or email address) which operates as the point through which data is deterministically stitched together in CJA. 

 

Working with an experienced digital partner like Netcentric can also help you to access a fuller return on investment from Customer Journey Analytics. Our experts help leading brands identify their principal business requirements, whether that’s analyzing marketing web traffic or connecting offline and online data as stores reopen in the wake of the pandemic. They then convert those into technical requirements and priority specifications and deliver the solution.

 

The first 360-degree data visualizer and analyzer is here. Get in touch today to discuss how your business can access insights from the entire user journey with Customer Journey Analytics.


Nicolas Athanasopoulos

Senior Customer Data Architect | AEP | CDP

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