Are you data-flooded, data-driven, data informed? Are you outcome oriented, insight driven or hindsight driven?
Are you a firm where executives claim – “Data is our competitive advantage.” Or sprout analogies like, “data is the new oil”.
The challenge I found in most companies is not dearth of vision… everyone has a strategy and a 100,000 ft general view of the importance or value of data. Every executive can parrot the importance of data and being data-driven.
The challenge is the next step….so, how are you going to create new data products? How are you going to execute a data driven strategy? How are you going to monetize data assets? What are the right business use cases to focus on? How to map the use case to underlying models and data requirements? What platform is a good long-term bet? The devil is in these details.
Everyone is searching for new ways to turn data into $$$ (monetize data assets). Everyone is looking for new levers to extract value from data. But data ingesting and modeling is simply a means to an end. The end is not just more reports, dashboards, heatmaps, knowledge, or wisdom. The target is fact based decisions, guided machine learning and actions. Another target is arming users to do data discovery and insight generation without involving IT teams…so called User-Driven Business Intelligence.
In other words, what is the use case that shapes the context for “Raw Data -> Aggregated Data -> Intelligence -> Insights -> Decisions -> Operational Impact -> Financial Outcomes -> Value creation.” What are the right use cases for the emerging hybrid data ecosystem (with structured and unstructured data)?
The core business problem that every retailer including Target is attempting to solve:
“Your loyalty cards and web application logs have captured all the activity in your stores, your Website and Mobile application. This data is priceless; for example, it not only contains the fact that a purchase has been made but also captures the thought process that went into making that purchasing decision. This session describes how you you can capitalize on this raw data to gain better insights into your customers, enhance their user experience, and make targeted recommendations.”
To provide insight into an approach…I am reposting this well written Best-in-Class Behavioral Analytics Case Study by Charles Duhigg on how Target is targeting customers using Predictive Analytics to anticipate shopper behavior.
Target was founded in 1902 and is headquartered in Minneapolis, Minnesota. Target operates over 1,750 stores in 49 states under Target and SuperTarget names. It offers general merchandise products through its Website, Target.com. The company distributes its merchandise through a network of distribution centers, as well as third parties and direct shipping. Additionally, it offers credit to guests through its branded proprietary credit cards.
Data Analytics and Influencing Pregnant Shoppers
Andrew Pole had just started working as a statistician for Target in 2002, when two colleagues from the marketing department stopped by his desk to ask an odd question: “If we wanted to figure out if a customer is pregnant, even if she didn’t want us to know, can you do that? ”
As the marketers explained to Pole new parents are a retailer’s holy grail. Most shoppers don’t buy everything they need at one store. Instead, they buy groceries at the grocery store and toys at the toy store, and they visit Target only when they need certain items they associate with Target — cleaning supplies, say, or new socks or a six-month supply of toilet paper. But Target sells everything from milk to stuffed animals to lawn furniture to electronics, so one of the company’s primary goals is convincing customers that the only store they need is Target. But it’s a tough message to get across, even with the most ingenious ad campaigns, because once consumers’ shopping habits are ingrained, it’s incredibly difficult to change them. Read more