Customer Journey Data Analysis

Customer journey data is a big business. In today’s market, customers are interacting with companies across many channels daily. Single touchpoint analytics fail to illustrate customer interactions in full. This has made way for a new kid on the block. 

To combat this problem, businesses should analyze the whole customer journey. Integrate segmented data to map service experiences from start to finish. Goodbye “old-school customer journey mapping”. Welcome “dynamic data connectivity”. 

More Touchpoints Means Better Data

Analyze more touchpoints across different channels for better data. This will let you optimize customer experience (CX) by using precision insights. By combining these real-time insights with data on customer behavior patterns, you can create a holistic customer experience plan. Combine this with an informed, engaged workforce, and you’ve got a winning strategy.

Gathering data about your customers on a single platform only tells you about their behavior on that platform. Whilst it will give you some idea of how best to target them, you’re missing out on the big picture.

In order to know your customer, you need to combine qualitative data with marketing metrics from multiple points in the customer journey. Customers approaching your website might engage with one product, but on social media, it might be something else entirely.

Taking all of these touchpoints into account will let you forecast with accuracy. By identifying optimal engagement times and successful marketing tactics, you can minimize customer churn.

Integrated Systems For Minimal Disruption

Customer journey analytics means easy data integration. By using data-based dashboards to inform your strategies, you can take the guesswork out of CX.

Today’s data analytics systems integrate into existing analytics infrastructures. Minimal hassle and no need for a costly total recall. If you integrate this new data into your pre-existing infrastructure, you can easily start to improve your digital PR campaigns and customer service. 

This all sounds great – but it’s time to take a step back. Using customer journey data boasts glittering heights. But how can we turn that data into smart decisions? Customer journey analytics are powerful. But to reap the rewards, they must be used wisely. 

Map Customer Journeys – But Don’t Stop There 

Traditional customer mapping is useful. But customer journey data takes mapping to another level. Analytics lets businesses track customer engagement touchpoints and act on them – fast! 

This is the best foundation for future business decisions. This quick, comprehensive data can be used to start implementing strategic changes. That might mean optimizing your checkout page, adjusting your social media strategy, or improving your website shopping cart. Your data will identify critical touchpoints and let you figure out where to act first.

One effective approach is to revisit existing customer maps. Separate them into smaller customer demographics along with different points in the customer journey. By doing this, you can break each part of the process down into trackable KPIs (Key Performance Indicators). Then you can install appropriate strategies for enhanced performance results.

Profile Using Web Analytics 

Marketing professionals today know that good CX drives sales. Customer journey data doesn’t just group customers according to their purchases. Journey analytics identify every customer  individually, based on their interactions throughout their journey with you. Businesses can then track and store invaluable data for future use. 

Data is a seriously great resource. You can use it to construct accurate customer profiles. A top analytics system will track and build individual customer profiles for you. Profiles based on real-time actions, behaviors, and preferences. 

Use this data to zoom in on unique micro-journeys. This is what KPIs and traditional customer mapping usually miss. Web analytics tools track customer journeys in different ways.

Some use clickstream reports to map customer pathways. This lets them identify the most popular route to a given web page. Others test customer pathways to see which routes end in most sales. In both cases, analytics tools help us get to know what works, and what doesn’t. 

A Practical Example: The Call Center 

Let’s turn to a more practical example for a moment. Imagine you operate a call center. Specifically, you’re running a contact center as a service (CcaaS). That means leveraging data from many platforms is important. 

Good CcaaS means integrating and analyzing customer interaction data across multiple channels. This allows you to identify and put in place much-needed service improvements. When successful, you increase customer satisfaction and enhance employee performance. 

Monitoring analytics will help you track customer satisfaction ratings. Technologies like cloud PBX (cloud-based Private Branch Exchange) systems often come with a whole host of tools that make monitoring this data easier than ever. Call recording, status reports, and integration with customer relationship management (CRM) systems allow you to build a complete image of customer interactions. 

This information can help you make smarter decisions. For example, you might realize that you’ve been receiving lots of calls about the same product or question. Now that you know this, consider adding that particular question to your site’s FAQs. By taking advantage of data, problems that would otherwise go unnoticed can be easily rectified.

Keep Up With Qualitative Data

Neglecting qualitative data is a common mistake. It’s tempting to focus on quantitative analytics, especially when introducing a new customer journey data system. Don’t be fooled. The cornerstone of improved customer experience is understanding customer feelings, thoughts, and preferences. 

Tools like omnichannel support solutions can help bring these insights to the fore. Keeping an eye on how happy customers are, key phrases they use, or survey feedback are all forms of qualitative data. 

Quantitative data analytics and qualitative customer experiences must be mutually informing. Only then will you know your customers on the micro and macro level. Only then will you understand your customer journey.  

Prioritize Personalization 

In the online marketing world, we’ve heard it time and time again. 

Personalization, personalization, personalization. 

Integrated data systems make enterprise 100% customer-centric. Try incorporating customer journey analytics or predictive dialer software into your CX strategy. This will convert leads into customers and increase customer lifetime value. 

Customer journey data should be your first port of call for personalized content. Instead of sending out generic emails on mass, use analytics to segment email marketing lists based on customer actions and behaviours. 

When customers receive content that is relevant to them, they are more likely to engage with it. Be smart with your analytics. Use data to know your users and then offer them a bespoke service in return. 

Pick your platform wisely 

Be savvy about the platform you choose. Not all systems are made equal. Your best bet is always choosing one based on your specific commercial needs. 

Systems that use AI and machine learning are particularly popular. Not only can they store a back catalog of past data, but they can use it. Data from past years can be analyzed, informing financial projections and future strategy. 

When choosing a platform, there are some key factors to consider.

  • What is the scale of your business? 

Larger businesses working with lots of data will need a CDP that is flexible, scalable, and offers excellent data security. Smaller businesses should focus on a CDP that offers long-lasting customer relationships via personalized campaigns.

  • Does your business have a physical location? 

Most commonly, e-commerce marketers choose no-code CDP (Customer Data Platform). These systems allow online retailers to track product details and integrate offline data with advertising platforms. Businesses based in a physical location would benefit from looking for data systems that use proximity-based marketing. These systems use location to target customers with personalized information.

Reach for the clouds

It’s worth considering a cloud computing server for your e-commerce business. IaaS SaaS PaaS might sound like a nonsense acronym, but they’re actually three main types of cloud computing. These options are popular for the management of off-premises IT systems. 

Ranking as the most popular model, making up 32% of enterprise usage, PaaS makes hardware and software tools available off-site. Having these tools available online reduces the number of calls that go unanswered and maintains consistent customer communications. It also means your staff can access customer journey data wherever they’re based.

Saas Vs Paas Vs Iaas
Via BMC blogs

What Next?

 Market mapping and isolated data samples are out. Today’s multi-platform ecommerce ecosystem requires an integrated data system to match. For now, customer journey data is the answer. 

By looking at every possible touchpoint, you can understand the entire customer experience journey. This lets you:

  • Locate and rectify trouble spots in the customer journey
  • Optimize already successful touchpoints
  • Personalize your customer interactions
  • Build comprehensive customer profiles
  • Convert more leads into sales

Customer expectations are mounting each day. Our data analytics systems need to match up. Customer journey data is the latest way to cover all bases. There’s never been more pressure to meet our customer’s expectations and there’s never been a better time to do it.

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About the author

Richard Conn is the Senior Director, Search Marketing for RingCentral, a global leader in unified communications and omnichannel contact center solutions provider.

He is passionate about connecting businesses and customers and has experience working with Fortune 500 companies such as Google, Experian, Target, Nordstrom, Kayak, Hilton, and Kia.

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