What s in Your Customer s Wallet? Best Practices to Grow Wallet & Market Share

Transcription

1 What s in Your Customer s Wallet? Best Practices to Grow Wallet & Market Share October 26, 2017 Featuring: Jonathan Bein, Real Results Marketing Richard Blatcher, PROS Thomas P. Gale, Modern Distribution Management Sponsored by: 1

2 About PROS is a cloud software company that helps competitive enterprises create a frictionless and personalized buying experience for customers. Learn more at 2

3 Speakers Jonathan Bein, Ph.D. Managing Partner Real Results Marketing Richard Blatcher Senior Industry Solutions Manager PROS Thomas P. Gale CEO & Publisher Modern Distribution Management/MDM Analytics 3

4 Our agenda Market analytics fundamentals Segmentation, methodology, end game Wallet share best practices Sweet spot analysis Customer lifecycle analysis Case study 4

5 Let s define wallet share Opportunity (unknown) Known Customer total spend Total spend for what you sell (account potential) Customer spend in category (category potential) Your sales in product category to customer Total $ spend on a product category in a given time period We need to find out the unknown: Use your data Ask the customer Use a model 5

6 Market and wallet share: Segmentation & models Market factors industry sector # of employees # of beds, trucks square feet Variables Product categories Territories Account firmographics Prospects Gross margin Profitability 6

7 The case for market and share analytics Benchmark / Targeting Focus resources on high potential Evaluate growth potential Sales force management Target high-potential segments/accounts Branch/salesperson guidance Branch/salesperson performance evaluation 7

8 Evolution of Market Analytics Time DEVELOPMENT Target, prospect, balance, align, manage ANALYTICS Benchmark, sweet spot, model SEGMENTATION SIC/NAICS, firmographic, behavior, life cycle, profitability DATA Taxonomy, cleansing, normalization, standardization, aggregation 8

9 Wallet share methodology Build model to verify current potential Internal: Customer transaction history External: Third-party market data Prospect locations Estimated total demand Safety PPE Employees at this location 9

10 Account profiling: wallet share Wallet share: Target Effective talent/time management 10

11 Market profiling / share analysis Major Gear Reducer Distributors Identify growth opportunities organic or acquisition Customer segments Identify oversaturated markets that yield lower margins Key in territory sizing (Branch vs satellite) Share calculation Market demand, competitor average sales/employees 11

12 Prospect concentrations Segment customers Find same types of prospects 12

13 Wallet share: Best customer Objective: Find sweet spots in your customer base that are high growth, high volume, high profit Method: Best Customer Profile is based on firmographic data such as SIC, geography, customer size, number of employees, profit Benefit: Focuses marketing and sales efforts on best opportunities 13

14 Wallet share: Sweet spots Executive intuition is imprecise due to Change in business climate downturn or upturn Exposure to customer base is often largest clients only Information about best segments is general, but no actionable Benefits of knowing sweet spots Builds on proven success for customer acquisition and wallet share growth Facilitates targeted messaging and campaigns 14

15 Relevant firmographic markers Industry sector NAICS, SIC, or custom line of business Customer size revenue, employees, location sq. feet Year of company founding Location state, city, county, zip, MSA Location type branch, headquarters, single location Number of locations Credit risk low, medium, high Manufacturing status yes or no Subsidiary status yes or no 15

16 Gross margin and operating margin When choosing a sweet spot, it is critical to know that there is zero correlation between gross margin and operating margin!!! 16

17 SIC 4-digit segments The graph shows customer segments by the three year compounded growth rate (CAGR) and sales volume in the last year. The trend is critical for identifying segments where is it easier to grow wallet share or acquire new business. 17

18 SIC 4-digit segments Growth Spend and Accounts CAGR Sales volume Average spend per account Spend opportunity Profitability Gross margin Operating margin (if available) Gross profit per order Average spend per order 18

19 Employee band segments For this distributor, customers with 1 to 10 or 10 to 50 employees are the best segments to pursue for volume and growth However, the 200 to 500 employee segment will involve a smaller number of customers since each customer spends more. 19

20 Employee band segments Growth 1 to 10 employee segments is growing very rapidly by accounts and spend Largest opportunity is in unspecified segment. Profitability Unspecified segment has very low gross profit per order Larger segments have higher gross profit per order than smaller ones 20

21 Year of founding segments This distributor is clearly winning customers who are newer businesses formed from the New Millennium until now 21

22 Year of founding segments The newer companies are lower average spend and lower gross profit per order Nevertheless, they have good gross margin and that is where the most opportunity is. 22

23 Find your best markers Extract at least 3 years of transaction data from ERP or CRM Get firmographic data from MDM Analytics, D&B, InfoUSA for customers Combine transaction and firmographic data Analyze by firmographic markers Select 3 to 4 markers that best predict growth and profitability 23

24 Customer lifecycle Recency-Frequency-Monetary (RFM) anlaysis is a powerful technique for organizing customer lifecycle management activities in marketing and sales. Customers are segmented by how recently they purchased and by the frequency of purchases. Sales and marketing actions vary by the cell as shown below. 24

25 Customer count There are 346 customers whose most recent purchase was 7 to 12 months ago and who only made 1 purchase. There are 75 customers whose most recent purchase is within the last month and who made at least 200 purchases. These are the best customers for this distributor. 25

26 Total spend Total spend is highly correlated not just with frequency, but also recency. The most recent and frequent customers will also have the best response rate to sales and marketing campaigns. There is typically a Pareto principle where a small set of customers comprises a large percentage of the revenue. 26

27 Total opportunity Opportunity Nearly $13M in largest 75 accounts More than $33M in accounts with 2 to 49 orders There is usually more opportunity in mid-size accounts since they are often underserved by multiple distributors 27

28 Classic view of RFM analysis Only a small percentage (such as 5%) of customers respond to the typical offer RFM tells you which customers are most likely to be in the responsive 5% If you use it all the time: Half your customers will never hear from you and will be lost Others will suffer from file fatigue Use it sparingly; when you need a boost Use it to identify your best customers 28

29 Current view of RFM analysis Use multichannel marketing to reach a broader set of customers than indicated in classic view of RFM Apply low cost marketing approaches, e.g. to lower recency, lower frequency customers Apply higher cost marketing approaches, e.g. outbound telemarketing or field sales, to high recency, higher frequency customers 29

30 Applications of RFM analysis Direct mail Outbound telemarketing marketing Web marketing Field sales Customer service representatives Technical support 30

31 What s in Your Customer s Wallet? Best Practices to Grow Wallet & Market Share Q & A Sponsored by: 31

32 What s in Your (Customer s) Wallet? Best Practices in Growing Wallet and Market Share: A Distribution Case Study Name: Richard Blatcher Title: Director, Industry Solutions Date: 10/26/ PROS, Inc. All rights reserved. Confidential and Proprietary.

33 CHALLENGES Not meeting revenue growth and profit goals Large Catalogue difficult for sales to represent Heavy reliance on sales reps experience Large number of customers knowledge gap 33

34 SOLUTION Refined Customer Segmentation Opportunities Delivered through existing workflows Allowed investigation Sales Reps maintained management 34

35 RESULTS Identified 110k potential opportunities 20k reviewed with 60% accepted Examples of 2X sales and unseating #1 competitor $6m annual incremental revenue 35

36 In summary Drive sales growth with existing customers Using machine learning to analyze transaction activity and identify new opportunities Found inconsistent purchasing behavior Found declining purchasing behavior Found gaps in product purchasing (cross sell) Automatically presented in CRM environments 110k identified, 20k reviewed, 60% accepted $6m incremental revenue 36

37 Contact Jonathan Bein, Ph.D Richard Blatcher

38 What s in Your Customer s Wallet? Best Practices to Grow Wallet & Market Share October 26, 2017 Featuring: Jonathan Bein, Real Results Marketing Richard Blatcher, PROS Thomas P. Gale, Modern Distribution Management Sponsored by: 38