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Small Business Analytics and Metrics:How and What Do you Measure Up?
Al Bessin, Principal, Bessin ConsultingGeoff Wolf, EVP Marketing , J.Schmid
Jude Hoffner, Principal, Hoffner Marketing
Overview
• The Challenge• Types of Data• A Customer-Centric View• Equalizing the Playing Field• A Basis for Comparison – Break Even and Contribution• Tips and Limitations
2
The Challenge
3
The Basic Business Proposition
• Don’t lose site of priorities
4
Classic View
• Marketing grouped around transaction channels• Planned, budgeted and measured independently
5
Spend Justification
• Catalog and internet marketing analyzed independently
• Different criteria applied• Customer behavior ignored
…a gross overstatement of program performance
6
Holistic Marketing Analysis Model
• Consider all channels together• Find common metrics to permit comparison
7
Types of Data
8
Categories of Metrics―Pre-Sale
• Website– Bounce Rate– Visitors– Page Visits– Entry and Exit Pages/Abandonment– Conversion Funnel
• Call Center– Calls Handled– Abandonment Rate– Talk Times– Upsells– Conversions
…what can be associated with customer records?
9
Categories of Metrics – Buying
• Push Marketing– Direct Mail– Email– Targeted Remarketing
• Pull Marketing– Paid Search (branded, competitive)– Natural Search (branded, competitive)– Direct URL Entry– Affiliate Programs– Marketplaces– Comparative Shopping Engines
…associated with customer records
10
The Channel Challenge• Consumer channel preferences are changing
– Website is a prominent element in the buying cycle• Enterprises remain organized around old models
– Direct Mail (or catalog) and Website Divisions– Call Center and Website Divisions– Should be Direct Division
• Consumers should see the enterprise, not individual channels
• Measurement and Analysis must look across the business
11
Data Types
• Ephemeral Behavioral Metrics– Useful for understanding interaction of different media– Not retainable at the customer level
• Persistent Transactional Metrics– Tied to the sale– Assignable at the customer level
12
The Problem
• Behavioral science is inherently “soft science”• There is no perfect quantitative answer
1. Use the 80:20 rule2. Be aware of opportunity cost
13
The Solution
• Collect Persistent Transactional data– Assignable to customer records– Quick view of channel and vehicle – Useful for predictive purposes
• Model response across channels• Adjust models with Ephemeral Behavioral trends• Validate models with testing
This achieves the quickest quantitative read on performance at a reasonable cost
14
Data Elements
• Systems need to be set up to collect source data• Codes should be passed along with orders to identify
direct sources
15
A Customer-Centric View
16
A Customer-Centric View
• Customers see brands and products and what they represent• Channels can have synergy or be in conflict
To maximize your relationship with your customers– Look at the business from their perspective
17
Customer Touch Points
Inducement
DecisionContact
TransactionFulfillment
DeliverySupport
Direct Mail MarketingInternet MarketingAdvertising
Call CenterWebsiteStore
Lifetime Value
18
Customer-Centric Data
• Persistent Transactional data permit customer-centric analyses
• Imperfect, but:– Generally predictive– Allow better contact relevance– Normalize the multichannel view
Critical to use a clean and accurate database
19
Equalizing the Playing Field
20
The Challenge
• Ban siloing – one team, one company• Aggregated Demand = 160%
21
Allocation Modeling
• Limitations as to what data can be collected that is customer-identifiable
22
Developing Models
• Start with collection of response data
• Customer identifiable• Estimate behavior• Model• Test to validate• Refine model
23
An Allocation Model
24
Key Takeaways
• Collect the data―all transactions should carry source codes
• Develop an allocation model• Test the model, ongoing• Measure ROI the same way for all vehicles• Use source information to plan acquisition and
contact strategies
25
Sometimes, “Simple” is Amazing
A Basis for Comparison
27
Calculating Return on Investment
• Demand $s (Matched Marketing Database)• GM% (plug)• Variable Transaction Cost (plug)• Marketing Cost (plug)
(Demand x GM% - Transaction Cost)
Marketing Cost
28
Breakeven Analysis - Defined
• “Incremental” Breakeven
The response rate at which the Order Contribution equals the Variable Marketing Expense
• Variable Marketing Expense includes only those costs which are truly variable (unlike a financial breakeven analysis)
For example: Do not allocate overhead such as CEO pay!
29
Breakeven Analysis
30
Tip:
• Transaction costs can be estimated by taking an annual P&L and dividing the variable expense by the number of orders taken !
31
Adding Observed Values
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Marketing Contribution
• Marketing Contribution is the Order Contribution less Variable Marketing Expense
• When Marketing Contribution on a first order is negative, it is the Acquisition Cost
• This establishes thresholds for selecting prospecting sources
33
Putting It To Work: 12 Month Contribution
• Measure the value of a customer in the 12 months after acquisition and compare to the acquisition cost
12 Month Order SalesLess: Cost of GoodsLess: Fulfillment ExpenseLess: 12 months of Marketing Expense
= 12 Month Value
34
The End Result: Sample Dashboard
35
Tips and Limitations
36
Attributes of Metrics
• Simple indicators of performance• Timely “heads up” to changes• Trigger more detailed
investigation
Avoid Analysis Paralysis
37
Frequency of Measurement
• Hourly• Intra-day variance
• Daily• Intra-week variance
• Weekly• Consistent time frame
• Monthly• Tie to monthly financials
38
The Role of Metrics
• Management to numbers• Budget• Rolling forecast
• Promote vision• Warning of sign of other issues
• Example - gross margin
39
Challenges
• Standards must be established for the individual business
• Information must be gathered from multiple systems
• Fewer significant metrics are better than more
• Information is dynamic• Never let metrics displace intuition
40
Be certain you understand…
• What drives demand for your business
• Your cost to acquire new buyers• The value of buyers and how it
differs by source• The impact of other factors on
demand
41
Final Takeaways
• Practical Attribution for Small Business• Statistics are not enough• Look High Level First • Test legacy • Look at Dependencies (example of chart that shows
orders timed with major marketing activities)• Internal benchmarking vs external• Why metrics must be tailored to the business –
attribution tuning
42
Questions?
43