- Web analytics
- Social analytics
- Predictive analytics
- Mobile analytics
- Mobile application analytics
- Content analytics
- Interaction analytics
- This list goes on
Then I thought it would be good to discuss how confusing it is for a marketer to use all of these different analytics, from one or more vendors, and tie together the insights they provide to create the consistent contextual customer experiences needed.
It’s true, there are a lot of different analytics, and the lines are blurring between them. And yes, marketers struggle to tie all the information together to get a cohesive view of the customer. But maybe even more important is the realization that analytics for the sake of reporting is simply no longer enough.
A conversation with Webtrends brought me down this path. Steve Earle, Senior Director, Product Marketing, Jeff Seacrist, VP, Product Management and Kathy Stromberg, VP Marketing took some time to discuss the current lay of the analytics land and how things need to change.
From web-centric to single point
We are marketing in a digital world. The Internet of Things (IoT) is just the latest in a never-ending stream of new touchpoints, both human and digital, that we have to manage. The data coming from these touchpoints is growing at increasing rates and many of today’s web analytics aren’t built to support the kind of technical data that is coming in from the Internet of Things.
The need for a data layer that enables access to all this information is critical if we want to provide highly relevant and contextual experiences.
There’s the second challenge for traditional web analytics vendors. Aggregate data isn’t good enough. If you want to leverage analytics to optimize the customer experience, then you need to have access to the data at the individual level, and it needs to be real-time, not historical. Also coming with having that individualized understanding of the customer are data security and privacy concerns.
It’s not just about marketing or e-commerce. Many web analytics solutions focus on the website, on campaigns and acquisition. But the customer experience extends far beyond lead generation and the sale. Marketing needs to analytics to track and understand our customers throughout the customer lifecycle, especially if they are ultimately responsible for the entire customer experience.
If analytics needs to move beyond reporting, then it’s reasonable to say that analytics is just one part of the picture. What’s the other part? Optimization. Optimization not by channel, but by customer journey.
Here’s how the Webtrends crew presented it to me:
From optimization by channel >> To optimizing the customer journey
From rear view mirror >> To driving personalization in the moment
From diagnostic analysis >> To actionable intelligence and accuracy at scale
This is a fundamental shift from web-centricity and silos of data to a single view of the customer.
The shift is not an easy one
This shift is not as simple as a technology change. It’s a process, skills and technology problem. The process and skills are organization specific. It’s about shifting the focus to the customer journey and understanding how your customers interact with your brand across the entire journey. I’ve talked about this before, so I don’t plan to get into it here.
But let’s look at the technology for a few minutes. What do you need to build what Forrester refers to as the “digital intelligence layer?”
“Technology that enables the capture, management, and analysis of customer data and insights to optimize digital customer interaction and experience across the customer life cycle.” – from the Forrester TechRadar: Digital Intelligence Q2, 2016.
Let’s break that down into the three primary technology categories:
- The data – the creation of a customer data warehouse in some form that marketers can access to get a single view of the customer.
- The analytics – the digital and predictive analytics required to get a real-time view of the customer across all channels and drive greater personalization.
- The optimization – testing and targeting capabilities not just for a single campaign or landing page, but across the entire customer experience, based on real-time analytics.
Forrester says there is no one vendor that provides all of the necessary capabilities, so it looks like integration continues to be a critical requirement for all organizations.
Tips for getting started – focus on proof points
You have to start somewhere. Seacrist said that organizations are investing in Hadoop (big data storage) to create a place that brings together all the data needed to attack individual problems. They are building the customer data warehouse. You need this before you can move forward.
Once you have this in place, think about your proof points – why is it required? Stromberg said to create some well-defined use cases with well-defined outcomes and show the organization that it works.
It wasn’t that long ago that I wrote a paper that looked at how you can get actionable insights from your analytics. It was, essentially, a primer on how you need to use analytics. But the bulk of the discussion was focused on reporting. Getting the information and reporting the insights.
We have moved way past that today. Traditional web analytics only tell us part of the story, and that story has tended to be a historical one. We need to put in place a set of technologies that give us a better view of the customer’s interactions with us across every touchpoint and improve that view automatically in real-time. Digital intelligence paints a much bigger, yet more intimate view of the customer and it’s time to shift the focus in that direction.
End note: I was going to talk about Webtrends new Infinity Analytics. It looks very interesting and worth reviewing. But I thought it would make more sense to do that in the context of what some of the other big analytics vendors are doing – like Adobe and Google. So that will be the topic of my column for next week.
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