At IBM Amplify, James McCormick, a Principal Analyst at Forrester discussed how to use Digital Intelligence to optimize your customer experiences.
First, James defined what is Digital intelligence – its just digital analytics, which is really just web analytics.
The Future of Big Data
With some guidance, you can craft a data platform that is right for your organization’s needs and gets the most return from your data capital.
The age of the customer is upon us, brought on by the winds of digital change. Customers now have more power in dealing brands, probably the most power they’ve had in history. Digital channels have made this easier for the consumer to engage with us, but also with our competitors and each other.
Now we are competing on the digital front-ends to compete for customers. Traditional analytics are ill equipped to help with this, because it is backward looking. We can’t really correlate analytics across all the channels and makes it hard to use them in the moment the customer shows up.
Digital Intelligence has evolved from web server log analytics, to web analytics, to digital analytics 2000 – 2011 was the golden age of web analytics – we thought we really understood customers by knowing what they did on the web site.
But then starting around 2011, mobile exploded. Offline behaviors became important too with mobile apps disconnected from our web sites. Social media also exploded and contained information like consumer intentions, perceptions, and sentiments.
Building your digital intelligence practice:
- Ownership Structure – hire and organize analytics staff to support digital business
- James found three types of structures: Centers of Excellence, Functional Alignment and Line of Business alignment. All of these structures were successful when aligned with the overall business structure. If a centralized business tried to implement a line of business analytics structure, it was less successful.
- Technical Approach – bring together multiple technical components for data mgmt, analysis, and action-ability
- Metrics & KPIs – collect a swath of measurements including those that help understand customers and gauge success
- You should layer metrics for a holistic customer view. There is a digital performance layer, which measures things like page views, etc.
- Customer experience measure look at how are customers tracking – what did they look at, what tripped a buy, etc.
- Customer relationship measures might include things like lifetime conversion measures, lifetime buy, etc.
- Optimization – apply a continuous optimization approach across the lifecycle.
- We should compete by delighting the customer at each moment of engagement. We have to learn from each moment to evolve the next moment. This is the optimization effort.
- This has to be done throughout the organization, not just in one department, one site or one retail location.
- You should consider the following dimensions of optimizations:
- Channels Optimized – are you optimizing only one or two channels? Which ones?
- Proportions of interactions optimized – how far have you optimized. Did you do the website? How about social? How many CSRs are optimized?
- Optimization techniques
- Customer lifecycle coverage – you should ideally optimize across the customer lifecycle, from discover, to explore, to buy, to use, to support
Digital Intelligence is proven. Here are some examples. Royal Bank of Scotland grew their team from 2 to 50 optimization specialists who then accelerated from 2 to 70 tests per quarter. The value of optimization tripled in the first year.
Shop Direct used digital intelligence to improve acquisition rates to 6% desktop and 3% mobile. They run 60+ tests per month and the goal is to fail fast, learn and evolve.
Here are three ways to accelerate Digital Intelligence:
- Make it a corporate strategy
- User partners to accelerate adoption
- Be agile an iterative
