Developing a customer marketing program
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This document discusses developing a customer marketing program in the "Age of the Customer" where companies need to have a proprietary view of individual customers rather than relying on generic third party data. It emphasizes segmenting customers based on their attributes and requirements in order to prepare targeted offers. Several approaches to customer segmentation are described, including clustering, ad-hoc analysis, and network theory. The key aspects of successful customer segmentation are that the segments are substantial, exclusive, accessible, timely, and different in characteristics in order to enable smarter business decisions, better marketing promotions, differentiation, and balanced growth. The conclusion promotes a software engine that automates sophisticated customer segmentation using network theory without large costs.
Developing a customer marketing program
- 1. Developing a Customer Marketing Program bd4hbig data for humans
- 2. “THE AGE OF THE CUSTOMER” In 2013 Forrester Research coined this phrase hailing a new era of marketing where customers where in control. It succeeded the “Age of Information” where companies like Google made sense of large amounts of data to navigate the internet. The Age of the Customer meant that companies needed a proprietary view of customers and could no longer rely on generic of third party information on prospects. Companies like Apple displayed an uncanny ability to anticipate customer requirements and become dominant In 2015 many retailers fail to know accurately who their customers are and what they want. When they can’t describe their customers from a unique perspective they fall back on third party information about the market they are in. This creates a massive risk and opportunity. But the solution lies under our noses in what people buy and how that changes every day. The Age of the Customer requires a new equilibrium in marketing and how we use big data. Winning companies will display an uncanny ability to anticipate customer requirements.
- 3. The New Equilibrium • Most digital business’ dominant source of data is their acquisition marketing program • The purpose of this data is to optimize acquisition metrics like CPM, CPA, Conversion Rate + add to that: • Customer Marketing requires execs to build strategy from the transacting customer outwards • Customer Marketing optimizes the revenue from people the business has already acquired = In the Age of the Customer success will be in the hands of those who best achieve this equlibrium Acquisition Marketing: Optimised to drive new customer volume and minimise Cost per Acquisition Customer Marketing: Optimised to drive Revenue per Customer, Lifetime Value, Profit per Customer and Retention Sales and Profit
- 4. Planning your Customer Marketing Segment Customers then analyse their requirements and attributes Segment Target Position Decide which groups of customers to target with offers or content Prepare offers which reflect customer requirements and activity levels
- 5. Customer Segmentation Approaches Clustering Ad-Hoc Analysis Network Theory Benefits Constraints Conclusion Relatively easy to perform Time consuming and highly subjective Not scalable for retailers with lots of product Replicable and actionable Skills heavy and complex to do well A better approach but “best fit” models hide outliers and date quickly Sophisticated and easy to interpret Complex to build and maintain Requires major data- science and computation resource
- 6. Customer Segmentation Success • Segments need to be substantial so that the are big enough to economically address • Segments need to be exclusive so you know which customer lives in which • Segments need to be accessible for instance by having customer identifiers • Segmentation needs to be timely because things keep changing • Segments need to be different in characteristics Smarter business decisions Better marketing promotions Basis for differentiation Balanced revenue and profit growth Respond to changing market conditions
- 7. Big Data For Humans software engine automates segmentation using network theory. Any retailer can deploy the most sophisticated method of understanding customers without the astronomical costs. It starts work on the transaction data that everyone has, providing rapid results across channels. Anyone in the business can use it to make smarter decisions and more profitable marketing. Getting started is simple. Our clients range from small businesses to global retailers, but they have one thing in common. They all make more money. We usually find some surprises too. The Age of the Customer Now bd4hbig data for humans