Using Data and Analytics to Build Audience and Revenue

Transcription

1 Using Data and Analytics to Build Audience and Revenue Mather Economics LLC November 3, 2016

2 Introduction to Mather Economics

3 Introduction Founded in 2002 by Mather Lindsay, PhD to bring leading practices in applied microeconomics to our business clients Clients in the United States, Canada, Europe, Asia Pacific, Australia with offices in Atlanta and Amsterdam 35 Employees and 10 academic affiliates Strong academic links to leading universities in the field of micro economics

4 Mather Economics Client Base 4 Clients include 17 of the largest media companies; across four continents Many of the largest subscription brands (600+ newspapers) Data analyzed on 30M print/ digital subscribers weekly Manage over $4B in subscription revenue annually

5 The Mather Economics Philosophy Assist our clients by managing their revenue relationships at the household or engaged user level through Data Collection Analytics and Practical Application A B Testing, Measure and Adjust Custom Reporting

6 Data Science: The future of our industry

7 Data is Oil Publishers need gasoline 7 Data is the new oil it s very valuable to the companies that have it, but only after it has been mined and processed. The analogy makes some sense, but it ignores the fact that people and companies don t have the means to collect the data they need or the ability to process it once they have it. A lot of us just need gasoline. Derrick Harris, Gigaom.com, March 4, 2015

8 What most publishers think about Data Science 8 What publishers think Too expensive, don t have the technological expertise We aren t ready to jump in the deep end The truth True, if you want to build inhouse. Ramp up is costly and takes time You can go slow and build as you identify opportunity Our team isn t savvy so the expense could be wasted Turnover is a risk if done in house so outsourcing is low cost option We don t have a fully baked vision of data science No one does, or if they do it s constantly changing We don t want to be the first one through the wall You are about 2 3 year behind so there are best practices

9 Applications of data science 9 Audience Holistic approach to the customer lifecycle Maximizing revenue yield Improving acquisition and retention strategies Creating a golden customer profile Advertising Dynamic metering First party data for targeted advertising Advertising rate optimization Content Staging content appropriately Revenue driven model

10 Holistic approach to all components of your revenue model Print Digital Targeted Subscription Pricing Audience Advertising Subscription Acquisition Dynamic Meter Advertising revenue yield management Dynamic rate card First party data Listener Digital Data Capture

11 Applications of data science 11 Audience Holistic approach to the customer lifecycle Maximizing revenue yield Improving acquisition and retention strategies Creating a golden customer profile Advertising Dynamic metering First party data for targeted advertising Advertising rate optimization Content Staging content appropriately Revenue driven model

12 Holistic approach to your Audience model 12 Acquire: Maximize start value/volume Retain Minimize churn Renew: Leverage willingness to pay Upgrade: Grow customer engagement Reacquire: Target offers based on history Reacquire Acquire Upgrade Retain Renew

13 Reacquire Acquire Acquire Upgrade Retain Renew

14 Acquisition Strategies 14 Revenue and Costs Leverage revenue and cost data to identify break even points for new subscriptions Predictive Analytics Layer on predictive modeling (probability of acquisition and retention over time) to acquire customers with both highest operating margins and highest conversion probability New Acquisition Strategies Newspapers are experimenting with multi year subscription offers, which maintain the offer price for longer in return for commitment Results have been promising thus far; retention has improved and new starts are up year over year

15 Acquisition Strategies: Using CLV to Enhance Conversion 15 CLV = [(Revenues Costs)*(Predicted Retention Probability)] [NPV] * Probability of acquisition 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Expected Lifetime (Area Under Curve) 18% 25% Bronze 17% 17% 23% Silver Gold Platinum Diamond

16 Acquisition Strategies: Analyzing Revenues and Costs Geographically 16 New offers can incorporate the longer term value of the customer (CLV), the probability of acquisition, and the probability of retention over time (3,4] (2,3] (1,2] [0,1] a=1 b=2 c=3 d=4

17 Acquisition Strategies 17 New Acquisition Strategies Case study has shown a 5% reduction in churn as a result of the multi year acquisition strategy

18 Acquisition Strategies 18 New Acquisition Strategies In addition to churn reduction, multi year acquisition strategy has increased paid circulation overall

19 Reacquire Acquire Retain Upgrade Retain Renew

20 Retention Strategies: Churn Modeling 20 Mather historically focused on renewal pricing Data driven method of optimizing renewal rates at the subscriber level Has effect of reducing pricing related churn vs. traditional flat increases, however: There still exists a churn problem Stops analyses showed majority of churn not related to price Validated through A/B testing How can Mather help our clients reduce non pricing related churn? Develop a model using existing subscriber data to estimate churn propensities at the subscriber level Markets can then segment market based on churn risk and take preemptive action to save at risk subs

21 Churn Modeling Output: Profiles 21 An effective scoring process allows you to customize your approach by risk/ opportunity Example below shows two subscribers, one at high churn risk and one at low churn risk

22 Retention Strategies: Churn Modeling 22 Using churn analysis to inform retention efforts Targeted marketing and communication tactics reduce churn, foster engagement and create a more effective expense model Combining churn and CLV scores allows market to focus resources on key customers CLV Score Retention and engagement campaigns Upgrade campaigns & aggressive pricing Retention calls, gift cards, aggressive campaign Standard retention campaign Churn Probability

23 Churn Analysis Application to Current Active Subscribers 23 CLV Score and Churn Score Churn Score CLV Score

24 Case Study: Applying Incentives to Churn Risk Accounts 24 Hypothesis: Incentives applied pre expiration will reduce churn on at risk accounts Results: Stop rate of treatment group was approximately 15% lower at 3 months; 10% lower at 5 months vs. control across upper third of estimated churn universe, even after several renewals (staying power)

25 Churn Modeling Case Study 25 Tracking churn targets over time shows the staying power of the incentive is quite strong Reduction in churn vs control remains relatively stable at the 60, 90, and 120 day marks post application

26 Case Study: Payment Data Driven Dynamic Messaging 26 Hypothesis: Targeting subscribers that have fallen outside payment window with dynamic messages will decrease non pay stops Results: Stop rate of treatment group was 14% lower versus a business as usual control group

27 Retention Strategies: Case Study Adjusting Touchpoints to Impact Expenses In this case study, payment analysis showed that the last five retention touchpoints netted only 7% of total payments Recommend replacing some of these late touchpoints with less costly alternatives and move date of 2 nd invoice up to realize revenue earlier 27

28 Retention Strategies: Conclusions 28 Key Takeaways A well defined churn model can successfully identify subscribers with higher propensities to churn The first rule of economics holds true: INCENTIVES MATTER! Providing incentives to subscribers to make payment results in lower churn levels (across all risk levels) Interestingly, the most expensive incentives aren t necessarily the most effective Targeted, personalized messaging (almost zero marginal cost) based on payment analysis insights results in higher pay through rates

29 Reacquire Acquire Renew (Revenue growth upon renewal) Upgrade Retain Renew

30 Renew MBP Program Review 30 Variable Pricing (Mather s MBP process) Variable pricing allows markets to meet budget goals while minimizing price related loss Target/control test groups are crucial to understanding the impact of Mather pricing One key metric is the incremental stop rate (target stops control stops) Benchmark: ~2.0% additional stops for every 10% price increase As markets have become more aggressive in 2016 incremental stops have increased, but at a lower rate than expected Review other key metrics, such as the price elasticity, to determine if pricing sensitivity has increase over time Analyzing stops can determine where pricing should be more or less aggressive

31 Variable Pricing: Goals and Comparison Goal = Balanced pricing: Other pricing approaches: Charging too high price causes churn and impacts brand negatively Cost Plus Pricing Set markup over cost applied equally to all units Competition Pricing Match competitors prices Customer Driven Pricing Focus on what customer indicate they are willing to pay Charging too low price for a premium product leaves money on the table and causes customers to discount the received value Variable Pricing Focus on the value that customers place on the product (which can change over time)

32 Variable Pricing Strategy Variable pricing means management of revenues and profitability on a subscriber level Pricing matches the customer s individual value of service Operating margins calculated for each account The price for each subscriber is analyzed at key points in their lifecycle Price suggestion calculated for each subscriber individually Customer s value of service changes over time as they move to new stages in the customer lifecycle Many factors used to build the model Customizable by client engagement Reporting compares actual revenue and cash flows to predictions for test and control groups

33 Price Points and Respective Subscriber Base 200, ,541 $25 Sub Count 175, , , ,000 75,000 50,000 25,000 $13.42 $ ,728 21,642 $ ,797 $ ,568 $ ,806 $16.90 $20 $15 $10 $5 Average Rate 0 Year 1 Year 2 Year 3 Year 4 6 Year 7+ Grand Total $0 Sub Count Average Rate Great opportunity to grow revenue incrementally as publication develops stronger relationship with the customer

34 Identifying Yield Opportunities Subscriber s weekly prices $9.00 $8.00 $7.00 $6.00 $5.00 $4.00 $3.00 $2.00 $1.00 Opportunities Areas under demand curve highlight the opportunity for improved yield $ ,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000

35 Subscriber Distribution post variable pricing model 35 $9.00 Twelve Months After Mather Launch $8.00 $7.00 $6.00 $5.00 $4.00 $3.00 $2.00 $1.00 $ ,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000

36 Renewal Strategies: Digital Engagement 36 How does online engagement affect retention of print subscribers, if at all? Listener tool captures online data to create a holistic picture of customer Listener data can enhance the effectiveness of print pricing by understanding how a customer s online engagement impacts print retention Example of Digital Engagement Groups 9,421 17% 11,900 21% 6,676 12% 7,261 13% 7,250 13% One and Out Unreliable Experimenting Weekly Plus 13,915 24% Consistent Interest Junkie

37 Renewal Strategies: Digital Engagement 37 Case studies have shown that digitally engaged subscribers have better retention relative to those with lesser engagement

38 Including digital engagement in pricing print subscribers 38 With a price change, digitally unregistered subscribers show 2.5% incremental stops Unregistered Price Elasticity: -0.17

39 Including digital engagement in pricing print subscribers 39 With a price change, digitally registered subscribers show 1.4% incremental stops Registered Price Elasticity: -0.09

40 Including digital engagement in pricing print subscribers 40 With a price change, digitally engaged subscribers show 0.8% incremental stops Registered Price Elasticity: -0.05

41 Renewal Strategies: Digital Engagement 41 Prior case studies have shown that the most digitally engaged subscribers can be priced on 3x more aggressively than those who are not registered Stop rate will be equal under this scenario Digitally disengaged subscribers can be priced less aggressively to save stops Layering in digital engagement enhances effectiveness of dynamic pricing Listener helps create a holistic picture of customers

42 Reacquire Acquire Upgrade Upgrade Retain Renew

43 Upgrade Strategies: Targeted Upgrades 43 Targeted upgrades using propensity modeling result in successful free and paid campaigns 5,400 Sample Size $9.99/month $12.99/month Low Cost Campaign to Test Telemarketing Test FREE and PAID Upgrades

44 Upgrade Strategies: Targeted Upgrades 44 Targeted upgrades using propensity modeling result in successful free and paid campaigns Sunday Only Subscriber Segment Offer Thursday + Weekend Upgrade Offer Sample Size Upgrades Conversion Beginning Post Conversion CLV VALUE Impact Total Value Gained $9.99/month LOW CLV Paid $12.99/month 3, % $ $ $ $ 33, $12.99/month HIGH CLV (key ZIPs) $12.99/month HIGH CLV (outside of key ZIPs) Free $12.99/month % $ $ $ (4.53) $ (910.53) Paid $14.99/month 1, % $ $ $ $ 11, TOTAL 5, % $ 43, EXPENSE $ 3, NET GAIN $ 39,917.59

45 Customer Lifetime Value Propensity to subscribe is key for maximizing response and long term value 45 Offer 1: SO for $0.49 / DS for $1.59 Address Key Sales Zone WP PP Rev P&I Deliv Cost Acq. Cost Age Income CLV X2000XXXX 20601Z A Older Uppermid X2307XXXX 20603Z B Middle Aged Uppermid XXXX 20171B C Older Wealthy The first subscriber actually has a higher acquisition CLV due to response and retention even though the operating margin is lower than the second subscriber The first customer shows an operating margin of $1.15 High propensity to subscribe = low weighted acquisition cost The second customer shows an operating margin of $1.28 Lower propensity to subscribe = higher weighted acquisition cost

46 Reacquire Acquire Reacquire Upgrade Retain Renew

47 Data Driven Reacquisition Strategies 47 Utilize data as well as your market knowledge Eliminate risk targets Maximize revenue yield with appropriate entry point points Create the proper sales mix Include digital engagement opportunities Test, measure and adjust

48 Takeaways

49 Getting started with Data Science: Takeaways 49 Build a vision (or at least a wish list) Identify risks/ opportunities Pick low hanging fruit Where are your easiest gaps to close Ask questions enough people are on the path already Other media companies Your leadership team Steal ideas and create your own Don t be afraid to fail Start small and build the right infrastructure for success Learn when you fail Test, Measure, Adjust

50 Circulation Health Assessment

51 Reacquire Acquire Profit Upgrade Retain Renew

52 Circulation Health Assessment 52 Expense as a Percentage of Revenue Lack of a Corporate Entity Expense Management Options vs. Raising Rates Distribution model Footprint management Transportation costs Sales and marketing Organizational structure

53 Circulation Health Assessment Circulation Department Overview 53 Home Delivery Observations Carrier Compensation Carrier Profit Margin Complaints Copies Per Route Number of Routes Management Structure Home Delivery Number of Subscribers Per Carrier Average Miles Per Route Geography of Market

54 Circulation Health Assessment Operations and Expense Management 54 Circulation sales, volume & supporting strategies Current Volume Trends Start Pressure Analysis Start/Stop Gap Evaluation Daily net Budget Variance Var % Last year Variance Var % Home delivery 27,542 28,100 (558) (2.0%) 28,356 (814) (2.9%) HD electronic 951 1,200 (249) (20.8%) % Single copy 6,295 6,851 (556) (8.1%) 6,855 (560) (8.2%) NIE print 2,345 1, % 1, % NIE electronic (200 (30.8%) % Third party % % Mail (36) (14.4%) 265 (51) (19.2%) Other (10) (10.5%) 95 (10) (10.5%) Employee % % Total daily 38,412 39,626 (1,214) (3.1%) 39,101 (689) 1.8%

55 Circulation Health Assessment Operations and Expense Management 55 History of subscriber rate Fluctuation by Tenure Market Comparison EZ pay Discounts Total Annual HD Volume Avg % of Total Volume Total Perm Stops CHURN Less than 1 yr 3, % 5, % Between 1 2 yrs 1, % 1, % More than 2 yrs 22, % 3, % 28,015 9, % Churn Billing cycles Proposed Billing Cycle RENEWAL SUBSCRIBERS -14 days 0 days 2nd RENEWAL GENERATED +22 days DM CONTACT Grace ends Tracking sales calls 1st RENEWAL GENERATED Expire date +10 days AUTOMATED REMINDER CALL +35 days+42 days Subscriber stops

56 Circulation Health Assessment ROI versus Cost 56 Mather will evaluate a large amount of operational, sales, and financial data and made comparison to industry standards as well as like sized properties. We will discuss the data and apply our analysis and market intelligence to those areas where we find to be challenges and opportunities. Establish sales plan and necessary metrics to monitor progress Detailed recommendations include anticipated savings/incremental revenue which will significantly outweigh the cost of our analysis.

57 Questions

58 Contact Information

59 Contact Information 59 Bob Terzotis Executive Vice President Mather Economics LLC 1215 Hightower Trail A 100 Atlanta, GA (337) office (719) cell