data

I originally published today’s post on Forbes. It appeared on their site on April 27, 2020.

Is it time for a brand refresh?

Data. It is being made out to be sexy – really sexy. Many folks even think that collecting mountains of data and stuffing it into CRM and/or marketing automation systems is the access to delivering great customer experiences. They are mistaken. 

In the Innovator's Solution, Harvard Professor Clayton Christensen argued that, during the early stages of an industry, firms with wholly proprietary products have the advantage. New technology is always glitchy, so engineering the entire architecture is the best way to ensure quality.

Thanks for coming along… to refresh your memory: three part series

·         Fixing The Suckiness of Predictive Analytics

·         Introducing Anticipatory Analytics

Journalism has been thoroughly disrupted over the past decade. News organizations, especially newspapers, have come under heavy financial pressure, news bureaus have been closed or consolidated and journalists have had to rethink their profession.

In Nate Silver’s Five Thirty Eight manifesto, he argues that the plural of anecdote is data. It is through compiling and analyzing observations that we transform ordinary experiences into scientific conclusions.

How do we take all the data we have and make some sense of it?

Continuing my CEM Toolbox series, today I'm sharing some tools to inventory and to bring your disparate data and data sources together in one place, to facilitate achieving that single view of the customer.

The modern world can be a dehumanizing place. Long gone is the sweet little old lady at the drugstore counter, replaced by big box retailers, brand logos and barcodes. We’re more often“handled” than serviced, calculated, rather than cared for.

The MIT Sloan Management Review recently asked Does Data Have a Shelf Life? According to the article:

The best part of my job is that I get to talk to people; lots and lots of people. I talk to so many people about the same subjects (in this case Customer Service) that I start to see patterns and trends emerge (I was told when I first started working at Gartner that two data points make a pattern and three make a trend – I’d like to think that it takes more than that, but you get the overall idea of how it works).