Customer Data — Are you already using customer-centric BEHAVIORAL ANALYTICS?
Don’t just track users — use data efficiently to analyze and optimize your company’s performance.
Welcome to the 2020's! This decade will be even more the era of smart data than the previous decades have been. While website statistics in the past mostly tracked page visits, page impressions etc., nowadays the goal is to learn a lot more about the users.
In our previous article on phygital experiences we already demonstrated the importance of hyper-connected ecosystems. To make these ecosystems work efficiently, behavioral analytics is a helpful tool.
What is behavioral analytics?
Customer Data is an elementary part of a customer-centric experience strategy. Behavioral analytics therefore is one of the core elements to create an Ultimate Customer Experience and to truly transform your company into a customer-centric one.
Whilst everybody is talking about data, it’s quite difficult to really UNDERSTAND data. It is not enough to just randomly collect as much data as possible from your users. Data is a very private and valuable asset — it’s already been called ‘the new gold’. So you need to very carefully define the data you want to acquire at which time, in which format, and — most important — what information you want to get out of it.
Defining the right smart algorithms just can’t be done in a day or so. Algorithms have to be defined based on your company’s very specific and individual needs. They can turn out quite complex and need to be fine tuned step-by-step on a fail-fast-learn-fast-basis to deliver optimal results.
1 — Define KPI’s and CPI’s
This is a major strategic topic. The definition of visions and goals of a business strategy directly leads to the definition of KPI’s (key performance indicators) within a certain project.
But since these indicators just show “reactions” of the users / customers to a certain product or service of the company, it is even more interesting to also define CPI’s (customer performance indicators), which measure the performance of the company and its relevance for their customers.
Examples of KPI areas:
- Websites / Portals / Apps (conversion rate, visitors, traffic sources etc)
- Content Marketing (shares, comments, backlinks etc)
- Social Media (followers, likes, shares, reach, growth etc)
- SEO / SEM (visibility, keyword rankings etc)
- Email Marketing (subscriptions, click through rate, bounces etc)
- E-Commerce (product recommendations, turnover, cancellation, return rate, cost per order etc)
Examples of CPI areas:
- Social Responsibility (customer satisfaction, data security / privacy, diversity, working atmosphere etc)
- Sustainability (reduction of CO2 emissions, recycling, upcycling, zero waste etc)
- Production (robotic, automation etc)
- Logistics (packaging, shipping, delivery process etc)
- Products & Services (availability, functionality, pricing, unpacking experience, support hotline, reward programs etc)
As becomes clear just by viewing this list, there are lots of dependencies e.g. between sustainability, production, and logistics. Or, between email marketing, social media, and user behavior on website portals and apps. Sure, it’s nice to see click rates rising. But what then, if you don’t know WHY this happens?
2 — Track behavioral data
Customer-centric behavioral analytics takes the data from both perspectives— not only from users / customers, but also from the companies themselves.
The more you track, the better you know which actions and services are really satisfying your customers, the better you can steer the success of your company.
With methods like data mining, cohort analysis, path analysis, customer dynamics etc. the main focus lies not on collecting single data points itself, but on making connections and dependancies of customer behavior alongside a customer journey / lifecycle visible — across all platforms within the ecosystem.
This last phrase is very important: don’t let different technical platforms interrupt or mess up your data flow. If you want to create and continuously improve your seamless customer experience, it is mandatory that you can refer to seamlessly connected data pools.
The quality of a good behavioral data analysis depends on the following factors:
- number of data points
- connections / dependancies in between data points (user flows)
- real-time data acquisition
- real-time data analysis
- conversion rate data-to-service
- competence of monetization
3 — Build customer-centric performance dashboards
Build dashboards to have an automated regular overview on all data stats. The dashboard can automatically set a baseline for “normal” behavior to provide you with immediate alerts for any “abnormal” behavior. It points out potential fields of action to derivate concrete action plans for optimization. A growth discovery engine can give you a quick overview on your company’s overall performance and potential new markets.
If you have managed to set up a hyper-connected ecosystem of products and services that provides your customers a phygital and seamless customer experience, then behavioral analytics will be a highly efficient way to ensure consistent quality and to leverage your business to the next level.
Want to learn more about data and how to create Ultimate Customer Experiences with it?
You may want to have a look at our previous articles on
Customer Centricity Transformation and Flywheel Business Growth Model or just stay tuned to coming up articles on Situative Relevance Index (SRI), Predictive Services etc… ;)
Get in contact:
Eve Cecon | Business Innovation Strategist @ Sensory-Minds
e.cecon@sensory-minds.com
