marketing roi measurement
TRANSCRIPT
Measuring and Growing the
ROI of Marketing
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Agenda for today
1. The critical questions to address2. Why are we here and what is the problem?3. Brief introduction to marketing effectiveness measurement.4. How to optimize marketing spend and maximize growth5. Questions and discussion
Measuring your marketing effectiveness:
Current Situation• Marketing Waste: Estimates consistently show
that 40-60% of marketing spend is wasted
• Marketing Expense: Is often the largest line-item expense on the balance sheet
• CMOs and CFOs: There has traditionally been tension on matters of marketing accoutability
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Some questions prompting need for measuring marketing effectiveness and ROI What are the most effective marketing channels – TV, Radio, Outdoor, FSI’s, Print or Digital?
What elements of my marketing investment are working and not working? Where is the waste?
What could we expect if we increased our marketing budget by $2 million and how should we spend it?
What has been the ROI of online/digital media versus traditional mass media?
What is the impact if we took a 3% increase in price?
What is the best way to allocate my marketing budget?
What are the primary growth drivers for our sales?
Why are we here?
• Marketing budgets tend to be one of the largest line-item expenses on the balance sheet. Understanding what you are getting for that is critical!
• Traditionally, there has tended to be no accountability for this expense. What do we get from this investment? Is there payback?
• According to a study by Proxima Consulting in 2015, “up to 60% of global marketing budgets are being wasted every single year!”. Finding this wasted spend is essential to the health of your enterprise!
• According to a recent study by IBM with about 1700 global marketing leaders, 63% of them believe that marketing ROI will be the most important and critical measure of business and marketing success in the next 3-5 years. Are you invested in your future success?
• The problem, however, is that only 16% of these marketers presently use marketing ROI as a guide to their marketing investment decisions. Where do you stand on this?
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1. You spend on a new
marketing initiative
3. Sales increase by X dollars and Profit Increases by Y%
Execute in Market
2. You take it to the market
In the ideal world
But things are not that simple
The problem: Too many channels, fragmentation and confusion
Sales
Competition
Weather
Service Quality
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…simply eye-balling historic media and sales data does not provide answers
1000 1100 1200 1300 1400 1500 1600303234363840424446
Sales and Retail Price
Sales
Pric
e
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Correlations and Data Relationships
Correlation = -0.71
Econometrics (marketing-mix modeling) is based on tested statistical relationships between marketing drivers and sales. Statistical correlation, as shown below, is the basic foundation.
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…econometrics (marketing-mix modeling) can helpA statistical technique used to identify and quantify the incremental contribution made by marketing
investments on sales & revenue
Sales
Macro-Economic
FactorsPenetrationOf Office or
Store Locations
Price
Owned & Earned (Social) Media
Promos/Direct
Marketing
Customer Satisfaction
Paid Digital Media (PPC,
Display)
Mass Media: TV, Radio, Print, OOH Involves collecting
this data over time
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The long & winding roadof marketing & the steps
to take
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Key Deliverables from Econometrics (marketing-mix
model) Projects
Oct-2010
Dec-2010
Feb-2011
Apr-2011
Jun-2011
Aug-2011
Oct-2011
Dec-2011
Feb-2012
Apr-2012
Jun-2012
Aug-2012
Oct-2012
Dec-2012
Feb-2013
Apr-2013
Jun-2013
Aug-2013
-200
0
200
400
600
800
1000
1200
1400
1600
1800 VarianceModelled SalesActual Sales
Units
Sol
d
Forecast
R2 = 97.6% - This indicates a very high level of accuracy to the actual sales data.Holdout R2 = 89.9% - This indicates fit for the forecast (holdout) test.MAPE = 4.2% The average % variance between actual sales and fitted/predicted.
Step 1: Develop a highly predictive sales modelDevelop a predictive model by mapping historic media activity (data) against sales. We deliberately holdout 10-15% of the dataset to test for predictive accuracy. The premise and validity of our models depends on validating predictive capabilities
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71.1
3.22.4
9.9
3.3
6.5
2.11.5 11.2
Total Incremental Sales Contributions for Company XYZ
Baseline Sales Paid.Digital-Search Paid.Digital-DisplayEarned-Social.Brand-Experience Owned-Website/SEO Paid SpotTVPaid Radio Paid Magazines Long-Term.Marketing Effect
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Step 2: Overall media contribution to sales
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Step 3: Marketing Variance: Drivers of Growth
Office Market Penetration
Pricing
Baseline Sales
Owned-Website/SEO
Paid.Digital-Search
Paid.Digital-Display
Paid Magazines
Paid SpotTV
Paid Radio
Long-Term.Marketing Effect
GDP Effect (Macro Economy)
-2.0% -1.5% -1.0% -0.5% 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0%
-2.0%
-1.9%
-1.0%
-0.4%
0.6%
1.3%
1.7%
1.9%
2.1%
2.5%
2.9%
Annual Variance Contribution
Below shows how company’s total 7.7% year-over-year growth is allocated across the marketing-mix and how each element affected this growth and business performance
Paid Radio
Paid Magazines
Paid SpotTV
Paid.Digital-Display
Paid.Digital-Search
$- $1.00 $2.00 $3.00 $4.00
$1.16
$1.24
$1.34
$1.73
$3.17
ROI per Dollar Spend for Paid Media
ROI per Dollar Spend
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Step 4: Returns by Paid Media Channel (ROI per $1 spent)The critical step in improving marketing productivity is a precise understanding of returns per invested dollar
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Step 5: Total Marketing Response
£- £1,000,000 £2,000,000 £3,000,000 168,000
168,500
169,000
169,500
170,000
170,500
171,000
171,500
172,000
172,500
173,000
Unit Sales Marginal Profit
Annual Marketing Spend
Annu
al U
nit S
ales Current Spend
Saturation
The dilemma is that incremental spend sometimes will not generate much growth because of saturation and diminishing returns. Marketing response tends to vary depending on the spending levels and competitive activities.
Oct-2010
Dec-2010
Feb-2011
Apr-2011
Jun-2011
Aug-2011
Oct-2011
Dec-2011
Feb-2012
Apr-2012
Jun-2012
Aug-2012
Oct-2012
Dec-2012
Feb-2013
Apr-2013
Jun-2013
Aug-2013 (500)
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500
1,000
1,500
2,000
2,500
Baseline Pricing GDP Paid.Digital-SearchPaid Magazines Paid.Digital-Display Paid Radio Owned-Website/SEOOffice Penetration Paid SpotTV Long-Term.Marketing Effect Earned-Social.Brand-Experience
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Step 6: Marketing Contributions by Month
Step 7: Marketing Spend OptimizationMarketing spend optimization generates an estimated +10.2% sales lift at constant budget levels (average of
past 2 years). This result restores some traditional mass media, but with a relative increase for digital. The
plan finances an increase of all other media via a reduction in spend on sampling.
CONTRIBUTION CURRENT SPEND OPTIMAL SPEND
Web SEO 442490400 134,555 639,447 Paid.Digital-Display 321811200 1,003,211 703,392 Paid.Digital-Search 429081600 677,888 959,171
Paid Magazines 201132000 134,211 383,668 Paid Radio 281584800 833,455 767,337 Paid SpotTV 871572000 3,611,152 2,941,457
0%20%40%60%80%
100%
Web SEO
Paid.Digital-Display
Paid.Digital-Search
Paid Magazines
Paid Radio
Paid SpotTV
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Total $6,394,472 $6,394,472
HOW WOULD YOU FEEL ABOUT GETTING 2 TO 8 PERCENT
MORE REVENUE WITHOUT REQUIRING SPENDING ONE
ADDITIONAL DIME ON MARKETING?
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Play out marketing What-if scenariosAn interactive dashboard allows you to simulate different marketing mix/spend
scenarios and assess the resultant impact on sales and profitability.
1. Set marketing budgets.
2. Set your spend levels across media channels
3. Assess the resultant impact on sales & profit
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Providing Answers to Business Questions
BOTTOM-LINE ANALYTICS: OUR EXPERIENCE
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It’s all About ResultsCompany Results
Coca-ColaBrought marketing ROI modeling to company for first time in 1996. In first year developed models for Coca-Cola, Coke Light, Fanta and Sprite in 12 Countries. Year two sales gains over prior year exceeded
$300 million.
StarbucksDeveloped measure of customer-brand experience using social media. Discovered that Starbucks main
strength lies in its in-store experience. Successfully developed brand positioning for Frappucino and Via Coffee. Sales growth improved from +7 to +11 percent
McDonald'sIdentified significant upside growth opportunity to drive higher restaurant sales by investing
significantly more in "dollar-value meals" one year after launch in 2005. Per recommendation, major & higher marketing investment in dollar value meals made McD's the growth leader in its competitive
segment for 2 years thereafter.
L'0realDeveloped models which measured the ROI across 12 different "Celebrity Spokespersons" in L'Oreal
Commercials. Recommended reducing number from 12 to 5 Celebrities, leading to growth improvement from +3 to +5%.
Hyatt HotelsDeveloped SEI to quantify measure of "customer satisfaction" derived from measures of Trip Advisor
hotel reviews across 300 different properties. This lead to a 5% improvement in customer satisfaction in subsequent year and a +6% growth in total bookings
AT&T Identified and quantified impact from the launch of iPhone. By identifying which ad copy messages were most effective, AT&T managed to increase it's wireless telecom market share from 28 to 30%.
Johnson and Johnson Developed analytic system for measuring and evaluating ad copy for Splenda brand. Enabled brand to reduce ad production from 8 to 4 commercial executions, saving $6 million
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BLA leadership bios
Michael Wolfe is CEO of Bottom-Line Analytics LLC in the USA. Michael has 30 years of direct experience in marketing science and analytics both on the client and consulting side. On the former, Michael has worked for Coca-Cola, Kraft Foods, Kellogg’s and Fisher-Price. He has also consulted with such blue-chip firms as AT&T, McDonald’s, Coca-Cola, Hyatt Corp., L’Oreal, FedEx and Starbucks. Michael has broad experience in marketing analytics covering marketing ROI modelling, social media analytics, pricing research and brand strategy.
Masood Akhtar is the Bottom-Line Analytics partner in the UK and heads the company efforts across EMEA. Masood is former Director of Analytics for McCann-Erickson and also has worked for Mintel International Group, JWT, Costa Coffee, Coca Cola, Hyatt Corp. He is an accomplished econometrician with extensive experience in marketing ROI analytics, marketing research, market segmentation, social media analytics and marketing KPI dashboards.
David Weinberger is CMO of Bottom-Line Analytics. David’s career has taken him to such blue-chip firms as Coca-Cola, Kraft Foods, Georgia Pacific and the Home Depot. David’s consulting experience has focused on such verticals as retailing, financial services, apparel, consumer products and insurance. David’s has considerable expertise in the areas of customer analytics, life-time value, shopper marketing, social media, brand strategy, segmentation and marketing ROI analytics.
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