Table of contents for Transforming your business with analytics
- Transforming your business with analytics – a series
- How to transform marketing with analytics
- How to transform customer retention with analytics
- How to maximize resource effectiveness with analytics
How to transform your marketing with analytics
Companies need to develop a loyal customer base and market effectively to them. But customers increasingly shop in multiple channels and formats, and have more choices than ever before. Your company can leverage the power of analytics to overcome these challenges. You can develop the capability to target customers with personalized marketing, building brand loyalty and increasing sales. What’s more, each step of this transformation —integrating disparate data sources to give a complete picture, creating a customer-centric perspective, micro-segmentation and ultimately personalizing marketing—creates value and improves outcomes.
Step One: Integrate Information
Most companies I work with still keep information in multiple databases with different regions or different divisions storing their own sales data. Product data is managed separately. To build a customer perspective that is actionable, step one is to map your sales to your product data, with analytics in mind. This means sales on a store-by-store, channel-by-channel basis at a granularity that allows for the analysis of sales by time of day or for “the week before Thanksgiving” and product data that is normalized across channels and captured to the package level.
Decision Management Edge: Begin with the Decision in Mind. Companies that collected and integrated the data they needed for a specific decision like ”is this product out of stock” had shorter implementation times than those with a more general approach.
Step Two: Build a customer perspective
Once a solid base of information exists about products and sales, the next step is to match it to customers. The goal is to tie all sales data to specific customers to create a customer-centric information set. Companies can then begin to see the kinds of customers they have and use this understanding to enhance their marketing campaigns, store layouts and more.
Decision Management Edge: Integrating the data for the decisions that make a difference to customer loyalty and profit realizes value more quickly than just aiming for a 360 degree view of a customer. Decision Discovery Services find and prioritize your customer decisions.
Step Three: Develop micro-segments
With customer sales and product data mapped to specific customers, you are ready to build analytical models. With your rich set of customer-centric information, you can now apply data mining and micro-segmentation. These analytical models will predict future customer behavior and develop fine grained segmentation or micro-segments. For example, predictive models can assess the likelihood that a particular customer will respond to a particular kind of offer or use the web channel.
Decision Management Edge: Companies that incorporated decisioning technologies like business rules in their front line IT applications achieved a higher ROI on their analytics investment. These companies are able to deliver analytic differentiation to their call center, their website and every customer interaction. Develop a Decisioning Technology Blueprint to operationalize your analytics.
Step Four: 1:1 marketing
The analytical models you have developed using your rich data set now enable truly 1:1 marketing. Companies who have reached step four are recreating the corner store using analytics. They are taking all the information they already have about all their customers, analyzing it and applying it so they can get to know and understand each individual customer. In the same way that the owner of a corner store knows every customer, their preferences and their needs, a large company can use analytics to deliver the same sense of connection at scale: a corner store with thousands, hundreds of thousands or even millions of customers.
Decision Management Edge: It’s now easier to get smarter and smarter about the decisions that matter to your customers. Decisioning technology like business rules makes it easy to evolve and change decision making without impacting the rest of your systems. Add predictive analytic models to support proactive decision-making and experiment with multiple approaches to find the optimal decisions for each “market of one”.
Each step along the way to transforming your business through analytics builds value. Companies at Step One can now do comparisons and planning across channels, geographies and store formats. At Step Two, with a solid customer centric information platform, companies can identify and link all information around a common definition of a customer. At Step Three, with customer information in hand, companies can create customer personas and increasingly fine-grained segmentation that allows more precise targeting of marketing. At Step Four, leading edge companies are using advanced analytics to recreate the corner store, delivering tailored offers and incentives that are personalized to each customer based on their past behavior and their likely future behavior.
Transforming your marketing with analytics is not some far off future vision. Companies today are crafting personalized, targeted offers at the point of sale and designing new customer-centric campaigns that increase revenue. Decision Management can be your edge in more quickly realizing the value of analytics.