As digital transformation paves the way for a more competitive marketplace for brands, customer experience has become an essential factor for every ambitious business to nurture.
To optimize the customer experience, brands must develop the best possible methods to collect, analyze, and act on the insights that customers produce.
According to Accenture data, 91% of consumers are more likely to buy from brands that offer relevant recommendations and deals, and this element of personalization can be championed through strong customer journey analytics.
How can your brand take its customer journey analytics to the next level? And what will the future of CX look like? Let’s delve into how to take extra care of your customer journey:
Care for Qualitative and Quantitative Data
The best customer journey analytics are driven by crisp, accurate, and expansive data. This raw data is the key to understanding your customers, but you must create a clear process for gathering and compiling your data from the appropriate marketing sources, channels, and localities.
For the most comprehensive overview of your customer journey, you need to find a synergy between qualitative and quantitative data. These datasets are defined as:
- Qualitative Data: This type of data is far more contextual, and helps brands to understand the ‘why’ and ‘how’ surrounding customer trends. Examples of qualitative data include feedback forms, customer surveys, and user testing.
- Quantitative Data: This refers to more voluminous metrics such as website visits, bounce rates, and sales figures. Platforms like Google Analytics typically excel when it comes to leveraging more quantitative data.
When it comes to aggregative qualitative and quantitative data, marketing data aggregation tools can be a great way of uniting various metrics and utilizing them to generate a more holistic overview of your customer journey.
Unify Customer Data Effectively
By unifying your qualitative and quantitative data in one place, a centralized digital system can automate the process of matching and merging data across multiple different platforms. This can help to save time and uphold higher levels of accuracy when it comes to database management.
Today, as multi-channel purchasing becomes increasingly commonplace, customer journey analytics have become more complex across industries. However, automation can empower each aspect of your service to deliver consistent brand experiences.
In the age of digital transformation, your insights must stem from more than just sales metrics. By unifying data effectively, you can add much needed context to your customer interactions and discover what’s driving their behavior.
Behavioral Segments Can Deliver Retention
Your customer journey analytics can be optimized further by utilizing behavioral segments to yield more information about specific customers rather than aggregating large swathes of data alone.
Churn may be inevitable for many businesses, but early lifecycle churn, such as when a customer cancels a service within a 30-day window or returns a product the next day, can be harmful because it indicates that the brand hasn’t been able to recoup its customer acquisition cost.
Behavioral segments can help you to better examine your sales and marketing funnel to analyze churn at the early, mid, and late-lifecycle stages for your customers. This will pave the way for more targeted marketing and reinforce the core value of your product on a more consistent basis.
This is likely to pave the way for increased customer investments in your brand with the help of journey analytics to shed more light on up-sell and cross-sell opportunities across your services.
Hunting For Your ‘Eureka’ Moment
Every successful customer journey involves a ‘eureka’ moment where they finally understand the value that your product will bring to them.
These moments are so important that failure to reach them will inevitably lead to them navigating away from your brand, possibly forever.
Unified customer journey analytics can help you to understand where your ‘eureka’ moment is most likely to be through spotting where purchase intent takes over from the evaluation stage in a customer’s journey across your various channels.
Identifying and amplifying your ‘eureka’ moment across channels is likely to generate more conversions and leverage better retention rates.
Unlocking the Future of CX Analytics
We’ve already been offered a taste of what the future will look like in terms of recent developments in artificial intelligence and machine learning. These innovations will move into the world of customer journey analytics to deliver more focused insights for businesses in real time.
AI and machine learning have the potential to analyze big data focused on customers as they are generated to identify patterns and insights that more traditional segmentation may miss.
This can pave the way for new and more focused segments while refining existing ones and creating more accurate customer profiles.
For example, brands will be capable of segmenting customers based on their past purchase behavior, website engagement, social media usage, and a series of other metrics that can be accessed with the help of artificial intelligence.
Platforms like ZoomInfo, a B2B database and sales intelligence platform, utilizes machine learning to deliver more focused segmentation based on the respective industries in which clients are based, company size, and various other metadata that can shape more focused retention measures.
This level of focused segmentation can help marketing teams to more effectively target their prospects and leverage more personalized campaigns based on the individual needs of each segment.
As digital transformation continues to ramp up the difficulty in outmanoeuvring competitors online, the ability to fine-tune and supercharge brand customer journey analytics will be essential in retaining customers for longer.
The post How to Supercharge Your Customer Journey Analytics for Optimized Retention appeared first on Datafloq.
