by Swati Sahai
The customer journey analytics market is expected to grow to USD 12.2 billion by 2022, at a CAGR of 20.8%, as per a new report by Markets and Markets. This explosive growth is taking place because companies are realizing that to become truly customer-centric, responsive, and insights-driven, they need to have a single unified view of their customer across channels.
Customer journey analytics is a lot more than a software solution—it is a whole new approach to marketing and customer experience. To do it right means to become customer-obsessed and not just customer-focused. Having said that, employing the right customer journey analytics software is a very good start to achieving your goal of becoming customer obsessed.
Customer journey analytics platforms vary widely in their capabilities and there is no one-size-fits-all solution. So, how do you choose customer journey analytics software that best fits your needs? In this blog post, I will help you define and prioritize the most important factors to include in your evaluation when selecting a customer journey analytics platform.
8 Factors to Evaluate When Choosing Customer Journey Analytics Software
Here are 8 things you should consider to help you select a customer journey analytics solution.
1. Document Your Business Goals
As with any enterprise technology purchase, the first step to a successful outcome is to spend some time thinking deeply about why you want a customer journey analytics software and what you hope to get out of it.
Here are the types of questions that will set you in the right direction:
- Why are you investing in a customer journey analytics solution? What are the key goals you and your team are looking to reach?
- What are the important customer journeys/use cases you are looking to discover?
- How many teams/people within your business have a need for this software?
- How will customer journey analytics software integrate with your existing marketing technology stack?
- What is your budget allocation for this solution?
2. Identify Your Data Collection and Integration Needs
The key to a successful customer journey analytics project is to ensure you collect and integrate data from your most important touchpoints and internal customer data silos. This data could be residing in data warehouses, point-of-sale systems, CRM solutions, marketing automation platforms, or being generated in the moment on websites, mobile apps and on social media.
The ability to quickly integrate data is an important feature of a customer journey analytics software. Data collection techniques include tag management, APIs, batch exports and direct integrations.
A good customer journey analytics platform sits as a relatively light layer above your existing martech stack without the need for re-platforming or throwing out any existing component of the stack.
To ensure you’ll be able to discover your customer’s most important omni-channel journeys, you should look for a vendor with a large set of integrations with commonly used martech tools for data management, content marketing, advertising, automation, social, etc. Many companies have critical customer data that resides in proprietary legacy systems, so you should make sure that this data can be integrated without requiring a lengthy custom software development project.
(Learn more about how a customer journey analytics platform can integrate your existing martech stack and make it better).
How quickly and painlessly a vendor can collect and integrate your data should be at the top of your list when you’re looking to choose customer journey analytics software. While most vendors take at least several weeks, there are some that can integrate your data sources in as little as 1-2 days. Ask for client references or do a pilot to ensure that data collection will be a fast and smooth process before you make your final decision.
3. Assess Identity Matching Capabilities
Matching identities across channels to build a unified, single view of the customer is a key element of the customer journey analytics process. Common customer identifiers include email addresses, customer loyalty IDs, device IDs, browser cookies, etc.
Many customer journey analytics solutions and Customer Data Platforms (CDPs) require all of the identity matching rules to be configured in advance. This greatly increases the amount of time and technical skills required to get to the point where you have data flowing and can produce meaningful insights.
Customer journey analytics solutions sometimes employ probabilistic matching, where a definitive identifier is missing or incomplete. It is important to gather session data across channels so as to build a customer record even for anonymous visitors. When an identifier is discovered, it enables correlation leading to progressive profiling.
Not all vendors have similar identity matching capabilities; some do not gather individual customer level data and some rely on clients to do the identity matching. The ability to match identities rapidly with often incomplete information across millions of data points is critical. Ideally, your customer journey analytics platform should be able to stitch together customer interactions over time, as customers progressively reveal more information, across multiple channels.
4. Prioritize Rapid Insights With No Coding
Due to the sheer number of data sources and the volume and complexity of data involved, the number of technologies impacted, and the need to take into account qualitative and quantitative inputs, customer journey analytics projects have the potential to take far more time and resources than you might anticipate. If marketing and CX teams will depend on the platform to orchestrate real-time, personalized engagement with customers through the ideal channel, then the rapid generation of insights will be a high priority for your organization.
How important is ‘speed to insights’ for your organization? Some vendors can deliver data collection, integration and customer journey discovery in as little as 3 days. Pay particular attention to how time and resource intensive the implementation process is for each of the tools in your shortlist. Ask how well the vendor supports clients not just during initial implementation but also with ongoing tasks such as adding new data sources.
After the system has been implemented, some customer journey analytics solutions are far better than others in quickly discovering and visualizing micro as well as macro journeys and identifying the most important journeys linked to quantitative metrics.
When it’s time to choose customer journey analytics software, look for a platform that has an intuitive user interface, caters for different types of business users and requires very limited technical skills and training. There are solutions in the market that enable you to build not only customer journeys, but also a wide variety of metrics, with no coding skills and no requirement of data scientists.
If rapid generation of customer insights is a priority for your organization, make sure to ask to speak to reference clients and explore case studies to ensure you are buying a product which will provide you with the greatest ‘speed to insights.’
5. Evaluate Journey Discovery and Visualization Capabilities
While both customer journey mapping and analytics solutions are designed to map customer journeys visually, there are significant differences between customer journey mapping and analytics tools. Journey mapping tools are great when you think you know the customer journey and simply want to create an attractive visualization.
However, when customer-facing employees put themselves in their customer’s shoes and try to imagine their experiences, it typically results in an imaginary journey that fails to reflect the variety of real-world paths your customers actually take. Visualization tools cannot help you to discover the real journeys your customers are actually taking, nor can they enable you to find the most important, high-impact journeys.
Discovering customer insights is critical for most companies, so evaluate whether each software solution on your shortlist enables you to discover and visualize your customer journeys. In this way, you’ll be able to uncover the numerous paths your customers actually take, as they engage with your company across channels and over time.
The quality of visualization of a tool must enable all the journey attributes to be quickly discovered, both basic ones such as events, duration, customer flow and advanced ones such as emotions or pain points. The best software should allow you to smoothly drill down from macro journeys to micro steps and understand all the related attributes.
6. Machine Learning and Predictive Analytics
To discover the most significant customer behaviors among millions of unique customer journeys requires advanced capabilities like machine learning and predictive analytics. When selecting customer journey analytics software, look for the strength of its predictive capabilities to test customer journey hypotheses, predict future customer behavior and automate engagement.
Some vendors have built advanced machine learning algorithms that help discover in-depth customer behavior across journeys and help slice it by most frequent behavior, most exclusive behavior and behavior most predictive of the desired outcome.
7. Determine Whether Orchestration is a Priority
Once you’ve discovered the most critical customer journeys, platforms that include orchestration (aka real-time engagement) capabilities can provide each customer with a personalized experience based on their own unique preferences and personal journey.
If orchestration is key for your organization, your customer journey analytics platform should be designed to make this possible. In addition to providing a means to discover and monitor customer behavior in real time, your customer journey analytics platform should enable marketing and CX teams to automatically engage with each customer at the best time, through their preferred channel and in a relevant, personalized way.
This can be achieved by embedding triggers at any point in a journey, so you can engage with each customer via their preferred channel (e.g. email, SMS, in-app message) in real time.
Once the event or interaction for triggering engagement is identified, your customer journey analytics platform should integrate with commonly used marketing automation tools, so you can engage with your customers through your existing marketing technology stack. The outcome is an enhanced performance level for marketing and CX campaigns through significantly better precision, targeting and timing.
When you evaluate customer journey analytics software, look for the strength of the product’s analytical capabilities for automating interactions in real-time.
8. Evaluate Ability to Measure, Monitor and Link Behavior to Quantitative Metrics
There are a number of ways that customer journey analytics can help you see the impact of customer journeys on your individual business. Customer journey analytics can provide a quantitative link from marketing or customer experience to hard metrics like revenue or profitability. A few examples of the kinds of journey-driven KPIs that you can visualize and monitor include:
- Customer acquisition, conversion and retention rates
- Average order size
- Repeat purchase rate
- Customer churn
- Marketing campaign attribution and performance
- Effectiveness of loyalty programs
This level of monitoring, though, needs to be simple, visual and intuitive. Look for a software that enables you to monitor insights in real time and over the long term through interactive dashboards and tables that can be customized easily. Evaluate how easy and quickly your team will be able to create reports and dashboards for important metrics through a drag-and-drop interface, that would otherwise take days and consume high-level data science resources to accomplish.
Now It’s Your Turn
Armed with this knowledge, you are now ready to better evaluate the wide range of customer journey analytics software platforms available. It’s time to pick the solution that will help your marketing and customer experience teams excel at understanding customer journeys, acquiring new customers and retaining existing ones.
Share your own experience in selecting a customer journey analytics tool (or any marketing technology tool) by leaving comments below!