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Data-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know
Mark Jeffery · 2010
In a sentence
A practical guide showing that focusing on just 15 essential marketing metrics lets any organization measure, justify, and radically improve marketing performance and gain competitive advantage.
Based on research of 252 firms capturing $53 billion of annual marketing spending, Mark Jeffery reveals a 'marketing divide' between the fewer than 20 percent of firms that practice data-driven marketing and the majority that do not—and shows that the leaders enjoy significantly better financial and market performance. Rather than overwhelming readers with 50 or 100 possible metrics, Jeffery distills the field to the 15 metrics everyone in marketing should know, organized as five essential nonfinancial metrics, four financial metrics (plus CLTV), and five new-age Internet metrics. With downloadable Excel templates, real case studies (Best Buy, Continental Airlines, Harrah's, DuPont, Microsoft, Royal Bank of Canada, Sears), and concrete strategies to overcome the five obstacles to data-driven marketing, the book equips marketers and non-marketers alike to quantify the value of marketing, justify spending, and become heroes in their organizations.
The four lenses
- Science
- Statistics
- Systems
- Strategy
The model
A causal model in which data-driven marketing capabilities (design levers) and organizational conditions shape psychological/behavioral states across the purchasing funnel (awareness, evaluation, trial, loyalty), which are captured by the 15 essential metrics and drive marketing and firm performance outcomes.
Data-Driven Marketing Capabilitydesign lever
The degree to which an organization uses centralized data, analytics, metrics, experiments, and infrastructure to manage and optimize marketing decisions in its day-to-day activities.
Marketing Measurement Designdesign lever
The practice of designing marketing campaigns for measurement up front by defining clear vision, key business objectives, metrics, scorecards, and tracking mechanisms before execution.
Experimentation and Targetingdesign lever
Use of small controlled experiments with control groups and analytic targeting (segmentation, propensity modeling) to isolate causality and direct marketing to the right customers.
Marketing Infrastructurecontextual condition
The technology and analytic systems—enterprise data warehouse, operational CRM, analytics, and marketing resource management—that collect customer data and enable scaled data-driven marketing.
Data-Driven Marketing Culturecontextual condition
An organizational culture with senior executive sponsorship, incentives aligned to results rather than activity, training, and transparency that supports adoption of data-driven marketing.
Customer Brand Awarenesspsychological state
The customer's ability to recall and recognize a product, service, or company, representing the awareness stage of the purchasing funnel where the firm earns first consideration.
Purchase Intent / Test-Drive Propensitypsychological state
Customer intent to purchase reflected in evaluative behaviors such as taking a test-drive, downloading trials, or simulating a product, serving as a leading indicator of future sales.
Customer Satisfaction (CSAT)psychological state
The customer's satisfaction and willingness to recommend a product or service to a friend or colleague, bridging loyalty and brand awareness as a golden leading indicator of future sales.
Customer Loyalty and Retention Behaviorbehavioral pattern
The behavioral tendency of existing customers to continue purchasing rather than defect, captured inversely by churn rate and driven by loyalty marketing.
Campaign Response Behavior (Take Rate)behavioral pattern
The behavioral response of customers accepting a marketing offer or call to action, captured by take rate, which drives customer acquisition cost efficiency.
Customer Lifetime Value (CLTV)outcome metric
The net present value of a customer's future profitability accounting for acquisition cost, margin, cost to serve, retention probability, and the time value of money, used to differentiate customer segments.
Financial Marketing Performance (ROMI)outcome metric
The quantified financial return on marketing investment measured by profit, NPV, IRR, and payback for demand-generation and new-product-launch marketing.
Firm Financial and Market Performanceoutcome metric
The organization's overall sales growth, profitability, and competitive market position relative to competitors, the ultimate outcome of effective data-driven marketing.
How they connect
- data driven marketing capability → predicts experimentation and targeting
- marketing measurement design → influences campaign response behavior
- experimentation and targeting → predicts campaign response behavior
- experimentation and targeting → influences customer loyalty behavior
- brand awareness state → predicts purchase intent state
- purchase intent state → predicts financial marketing performance
- customer satisfaction state → predicts customer loyalty behavior
- customer loyalty behavior → predicts customer lifetime value
- campaign response behavior → predicts financial marketing performance
- customer lifetime value → influences firm performance
- financial marketing performance → predicts firm performance
- data driven marketing capability → predicts firm performance
- marketing infrastructure → moderates experimentation and targeting
- data driven culture → moderates data driven marketing capability
A candidate measure
Data-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know — derived measurement candidates
Data-Driven Marketing Capability
percentage of campaigns with business cases; MCM maturity stage; share of marketing guided by analytics
self-report suitability: medium
Marketing Measurement Design
proportion of campaigns with scorecards; presence of KBOs per campaign
self-report suitability: medium
Experimentation and Targeting
number of experiments per period; percentage of targeted vs mass marketing; measured campaign lift
self-report suitability: medium
Marketing Infrastructure
infrastructure capability tier; data integration breadth across functions
self-report suitability: low
Data-Driven Marketing Culture
staff-reported skill gap; incentive alignment rating; sponsorship presence
self-report suitability: medium
Customer Brand Awareness
unaided recall percentage; aided recognition percentage; brand linkage percentage
self-report suitability: high
Purchase Intent / Test-Drive Propensity
number of test-drives; test-drive-to-sale conversion rate; intent-to-purchase score
self-report suitability: high
Customer Satisfaction (CSAT)
percentage highly satisfied (9-10); net promoter score; future-spend intent
self-report suitability: high
Customer Loyalty and Retention Behavior
annual churn rate; 30/90-day churn; repurchase rate
self-report suitability: medium
Campaign Response Behavior (Take Rate)
take rate; click-through rate; transaction conversion rate; acquisition cost
self-report suitability: none
Customer Lifetime Value (CLTV)
NPV of customer profit; retention probability; product portfolio depth
self-report suitability: none
Financial Marketing Performance (ROMI)
NPV; IRR; payback period; profit
self-report suitability: none
Firm Financial and Market Performance
year-over-year sales growth; net income; relative market share; stock performance
self-report suitability: low
The story
The reader A marketer (or non-marketing manager) who wants to significantly improve marketing performance and justify marketing spending.
External problem
Marketing budgets are being cut and marketers must justify their spending and prove the value they create.
Internal problem
They feel overwhelmed by data, skeptical of their own ability to measure 'fuzzy' branding, and tired of going to executive meetings with no concrete answers.
Philosophical problem
It's just plain wrong that marketing should be treated as an unmeasurable cost center when its value can be quantified and managed like any other business function.
The plan
- Define a data-driven marketing strategy and collect the right 20 percent of data that gives 80 percent of the value.
- Overcome the five obstacles—getting started, causality, lack of data, resources/tools, and people/change—by scoring quick wins and running small experiments.
- Apply the 15 essential metrics, choosing the right metric for each marketing activity using the behavioral impact model and a balanced scorecard.
- Use financial ROMI (profit, NPV, IRR, payback) and CLTV to quantify value where applicable, and nonfinancial leading indicators where it isn't.
- Build infrastructure incrementally, create a data-driven culture with aligned incentives and training, and review results in a flexible process.
Success
- Marketing spending is justified with concrete data and a track record documented in scorecards.
- Marketing performance improves dramatically (often by factors of five or more) through targeting, experiments, and value-based strategies.
- The marketer is recognized, promoted faster, and gains respect and a seat at the boardroom table by speaking the language of finance.
At stake
- Marketing is viewed with skepticism and is first to be cut in tough times.
- The firm gradually loses market share and profitability, ending up eaten by competitors or going out of business (e.g., Circuit City's 'death spiral').
- Money is wasted on unmeasured, money-losing campaigns and negative-value customers go unnoticed.
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