Tag Archives: business insights

Marketers Can Use Big Data By Applying Their Strength: Storytelling

What do all marketers have in common? Marketing guru Seth Godin famously said that all marketers are storytellers. Stories, not features and benefits, sell.

Anyone who buys a slightly more expensive brand of laundry detergent because it’s “better” proves this. Godin wrote that if someone buys shoes because he or she wants to be associated with a brand that is “cool,” that brand successfully told its story to the right market.

Big Data and Storytelling

Big Data and Storytelling

A story has heroes we identify with. It has a conflict, which the heroes try to overcome. A good story’s DNA is an ordinary person in unusual circumstances. When is the last time you had an u­nusual result from your marketing campaigns? Perhaps a pay-per-click ad does poorly in your A/B testing. Or, there’s a high bounce rate from your latest email campaign.

Many marketers aren’t data scientists. But savvy marketers know they have to deal with big data, since it has become a hot topic central to many businesses. Marketers simply want to do their jobs better — and big data should be seen as an opportunity, not a hindrance.

When you have big data that could unlock great insight into your business, look beyond complexity and start with your strength as a marketer: Storytelling.

To get you started, I took the needs of marketers and applied them to these “who, what, why and how” principles from a recent article in the Harvard Business Review by the author of Big Data at Work, Tom Davenport:

Who is your hero? He or she is likely your prospective or existing customer.

What problem did the hero have? This is the action of the story. Here’s a real-life example from the Harvard Business Review article: Your hero visits your website, and adds items to the shopping cart. However, when you look at your analytics dashboard, you notice he or she never finishes the transaction.

Why do you care about the hero’s problem? Identifying with the hero is important for a story’s audience. It creates tension, and gives you and other stakeholders the incentive you need to dig into your data for a resolution.

How do you resolve the problem? Now you see what big data can do — it solves marketing problems and gives you better results. In the abandoned shopping cart example, the company found that people in Ireland were not checking out. The resolution came from the discovery that the check-out process asked for a postal code. Some areas of Ireland have no postal codes, so visitors would give up.

Remember it’s possible that the data itself is the problem. If you have bad contact data, you can’t reach your customers. Find the source of your bad data, and then you can return to your marketing efforts with confidence.

While big data may sound complicated or messy, if you have a storytelling path like this to take, you can find the motivation you need to uncover the powerful information required to better engage with your audience.

Engaging your audience starts with having accurate, validated information about your audience. Marketers can use data to fuel their campaigns and make better decisions on strategy and planning. Learn more about data quality management in this white paper.

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Building A Better Data Warehouse

The devil, as they say, is in the detail. Your organization might have invested years of effort and millions of dollars in an enterprise data warehouse, but unless the data in it is accurate and free of contradiction, it can lead to misinformed business decisions and wasted IT resources.

We’re seeing an increasing number of organizations confront the issue of data quality in their data warehousing environments in efforts to sharpen business insights in a challenging economic climate. Many are turning to master data management (MDM) to address the devilish data details that can undermine the value of a data warehousing investment.

Consider this: Just 24 percent of data warehouses deliver “high value” to their organizations, according to a survey by The Data Warehousing Institute (TDWI).[1] Twelve percent are low value and 64 percent are moderate value “but could deliver more,” TDWI’s report states. For many organizations, questionable data quality is the reason why data warehouses fall short of their potential. (more…)

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