Unlock the gold-mine of customer transactional data from POS system, loyalty or credit card programs and turn it into highly actionable “knowledge” to get a clear picture of the critical factors with the greatest implications to drive profits and reduce costs.
Identify where to best focus marketing dollars for targeted media and broad reach media to increase mind-share, wallet-share and sales.
Through the use of MFD Analytics and Customer Targeting, you will realize significant lifts in program response and cost savings. These performance improvements have been recognized through a suite of Target Analytical Tools:
- Customer Value Analysis, Clustering and Profiling
- Sophisticated Predictive Modeling
- Flyer Program Optimization
- Information acquisition and management
Ensure the thousands of dollars spent on planning, creative and printing return the highest possible dollar by targeting only those potential customers or market areas that will produce required returns. Overcome the problem of vague and often obsolete information by effectively matching targeted objectives and delivery resources.
Design flyer and marketing programs to solve any number of retail objectives:
- National, regional or local flyer campaigns
- Problem store marketing
- Ethnic marketing
- Seasonal marketing
- Special ‘value customer’ or development marketing
- Competition blunting
- New store or new market area development
Analysis for Profit Based Targeting
The key to establishing a profitable distribution to optimize marketing strategies and objectives, is the understanding of the Store Market Area (SMA).
Store Market Areas are the geographies that drive the highest sales and profits for each store and therefore dictate the most efficient distribution areas. Within the SMAs are the micro Cluster Areas of relative sales strength that dictate granular level targeting.
SMAs may be targeted themselves or aggregated to form larger market areas. SMAs and optimized distribution areas are developed utilizing one or more analytical processes depending on available data and marketing objectives:
- Sales Value Clustering Analysis
- Drive Time Analysis
- Geographic Analysis
- Demographic Analysis
- Consumer Spending Potential
Layering Sales Response, Drive Time and Distance Analysis can provide a fairly definitive SMA and the best areas to target – scaleable to budget and program objectives.
Results of the analysis are revealed graphically both cluster or group level and from an aggregated total of the groups. This allows retailers to assess the value of the clusters and make more educated decisions on the results of targeting.
Demographic Targeting
Store Market Areas will be composed of a number of consumer clusters comprised of distinctive demographic and socio-graphic profiles. Understanding these clusters and their demographic makeup allows marketers to target their messages with greater relevancy and find new areas that are of the same makeup.
Going Deeper with Analytics
Data Mining and Predictive Modeling
Data Mining removes the randomness and uncertainty of target marketing. Go deeper into your data for better, more predictive results. From simple data queries to the most sophisticated "machine learning" techniques, Data Mining is the process of analysing large databases and extracting meaningful, actionable knowledge. Hypothesis Testing and Knowledge Discovery, the two basic forms of Data Mining, uncover insights into past and current customer trends and patterns.
Predictive Modeling enables the marketer to apply those insights and tighten the future focus on customers of highest potential and value.
Response Modeling
The analysis of customers' previous purchasing behavior over a logical period of time, to allow:
- Higher returns from smaller segments of database
- Removal of direct-mail "randomness"
- Higher response for equal dollars
- Improved ROI per marketing dollar
- Savings on communication costs
Segmenting & Profiling
Advanced statistical methods of clustering, and producing decision trees used to understand customer segments and purchasing behaviors, to:
- Establish and understand strategically meaningful clusters of customers or prospects
- Identify archetype customer per cluster
- Understand clusters' differentiating characteristics
Customer Valuation
Predicts the future value/profitability of a customer or customers, permitting:
- Early identification of customers likely to be most profitable over the long-term
- Identify upsell prospects/opportunities
- Enhanced ROI per marketing dollar
- Improved preferred-customer programs and customer retention
Cross-Selling Model
Predicts what customers are most likely to buy, based upon purchasing history. This allows a marketer to: Maximize up-sells while minimizing costs of procuring new customers Generate more sales for the same or fewer marketing $$ Improve inventory control and supply-side management.
Note: We have merely scratched the surface here. For detailed information, click here for: "Data Mining and Predictive Modeling - A Practical Guide for Retailers and Direct Marketers."
Performance Measurement and Benchmarking
Post program performance analysis is the ultimate report card on your targeted efforts, and is the critical link to ensuring the continual Optimization of any flyer or direct mail program. MFD’s dashboard of Performance Measurement analysis ensures programs are financially accountable.