Analytics and data are transforming companies around the world. Yet one of the great difficulties with Analytics is that it can be difficult to explain and understand; it is widely held that analytics specialists don’t communicate well with decision makers, and vice-versa. As a result, analytics adoption is still not easy within companies.

Analysts, at one end, are busy learning more specialised & deeply technical methods of analysing data & at the same time they are finding it difficult to get them “heard” within organisations. Influencing ultimate decision makers is similar to selling products or services to external customers.

Analysts need to understand that when they present ideas to decision makers, it is their responsibility to sell – not the decision maker’s responsibility to buy. Rudyard Kipling once wrote that if History was taught in the form of stories, it would never be forgotten.” In her persuasion & power of story video, Stanford University Professor of Marketing Jennifer L. Aaker explains that stories are meaningful when they are memorable, impactful and personal. Have a look at this wonderful story told by Jennifer.
http://bit.ly/1iqcvin

Stories are the best way to influence! But we don’t see them being used so often. Analytics doesn’t need you to solve only a technical problem but a “social” one. Analytics is sexy but for it to make an impact, it needs to be embedded into the fabric of the company. This calls for analysts to become more social & in fact better presenters & story tellers.

They need to learn to demystify analytics & link it to practical ways for the business to make money! And analysts need to learn to link their work to “the last mile”. Analytics should not be expected to deliver a “Aha moment”, instead it should be a “factory approach to improved decisions”. So analytics is not just a planning tool as much as it is an Execution tool to improve the customer experience & business impact. Start with a decision in mind & work backwards, not with the data in mind & working forward. And today with reams of external data available to most marketers, analytics can even mash up different kinds of data & improve the Customer experience.

Compare the analytics industry with the world of journalism. One of the most deadline filled industries in the world is getting it right with what it calls precision journalism! Despite crazy deadlines, I am amazed at the powerful stories journalists write using data. I wish the analytics industry was half way as good!!The corporate world needs to learn from this & use data to tell stories better! Journalists are coping with the rising information flood by borrowing data visualization techniques from computer scientists, researchers and artists. Some newsrooms are already beginning to retool their staffs and systems to prepare for a future in which data becomes a medium.

Analysts are often tempted to communicate how they did the analysis: “First we removed the outliers from the data, then we did a logarithmic transformation; that created high autocorrelation, so we created a one-year lag variable”—& the typical business user is already yawning! The audiences for analytical results don’t really care what process you followed; they only care about results and implications

Here is an example of a master storyteller. Many people employ static charts, but visual analytics are increasingly becoming dynamic and interactive. Hans Rosling, a Swedish professor, popularized this approach with his frequently viewed TED Talk that used visual analytics to show the changing population health relationships between developed and developing nations over time. Rosling has created a website called Gapminder (www.gapminder.org) that displays many of these types of interactive visual analytics

In early 2010, The New York Times was given access to Netflix’s normally private records of what areas rent which movies the most often. While Netflix declined to disclose raw numbers, The Times created an engaging interactive database that let users browse the top 100-ranked rentals in 12 US metro areas, broken down to the postal code level. A colour-graded “heatmap” overlaid on each community enabled users to quickly scan and see where a particular title was most popular.

See more at: http://nyti.ms/1iCAQnp

Brent Dykes has this wonderful take in a Forbes article & I quote:

“It’s important to understand how these different elements combine and work together in data storytelling. When narrative is coupled with data, it helps to explain to your audience what’s happening in the data and why a particular insight is important. Ample context and commentary is often needed to fully appreciate an insight. When visuals are applied to data, they can enlighten the audience to insights that they wouldn’t see without charts or graphs. Many interesting patterns and outliers in the data would remain hidden in the rows and columns of data tables without the help of data visualizations.

Finally, when narrative and visuals are merged together, they can engage or even entertain an audience. It’s no surprise we collectively spend billions of dollars each year at the movies to immerse ourselves in different lives, worlds, and adventures. When you combine the right visuals and narrative with the right data, you have a data story that can influence and drive change”.

Also today Marketers have access to a lot of external data. How they mash this up creatively with their own data & produce features that are of value to consumers is going to become very important in the days to come.

Here is an example:

How Airbnb can add more value to its consumers?

New York City noise complaints not only to map out which neighbourhoods were noisiest, but why they were noisy.

From the screenshot above, you can see that you’ll definitely want to steer clear of two neighbourhood near the Bronx if you hate the sound of ice cream trucks.
How can this help a Marketer?: Imagine if this led Airbnb to import this data & use it to help you in selecting a place to stay. I am fresh from staying in Singapore in an Airbnb apartment which was in a noisy neighbourhood. If this can be created into an index which pops up as I view an Airbnb apartment, it adds another data based layer to my decision of which apartment to choose. You can enhance this with other data like Crime in the neighbourhood etc & suddenly data is actually adding much more value to the AirBnB platform.
So if data based storytelling can be linked to “How customers buy” , that can hugely enhance a customer’s experience & value. Think about how you can do this in your business & use storytelling to impact key decisions in your company & also your customer experience.