Implementing Marketing Analytics Implementing Marketing Analytics Outline Potential

Implementing Marketing Analytics

Implementing Marketing Analytics Outline § Potential benefits of vs. skepticism toward marketing analytics § Empirical evidence about the performance implications of deploying marketing analytics § Putting it all together

Implementing Marketing Analytics Challenges faced by today’s marketing decision makers § Global, hypercompetitive business environment. More demanding customers served by a greater number of competitors on a global scale. § Exploding volume of data “We’re drowning in data. What we lack are true insights. ” § Need for faster decision making Information overload and lack of time, yet decisions have to be made all the time. § Higher standards of accountability Marketing expenditures have to be justified in the same way as other investments.

Implementing Marketing Analytics Need for better marketing decision making § Intuitive decision making □ In a world characterized by rapid change, information overload, greater accountability, etc. intuition is unlikely to generate superior results; § Data- and model-based decision making □ Marketing Engineering: “A systematic approach to harness data and knowledge to drive effective marketing decision making and implementation through a technology-enabled and model-supported interactive decision process” (LRB, p. 2) § Yet, “paralysis through analysis” and other criticisms of marketing analytics

Implementing Marketing Analytics Marketing Engineering Marketing Environment Marketing Engineering Data Information Insights Decisions Implementation Automatic scanning, data entry, subjective interpretation Database management, e. g. . , selection, sorting, summarization, report generation Mental models, Decision models Judgment under uncertainty, e. g. . , modeling, communication, introspection Financial, human, and other organizational resources

Implementing Marketing Analytics Germann, Lilien, and Rangaswamy (2013)

Implementing Marketing Analytics Data analysis § Familiarize yourself with the questionnaire and the data (i. e. , make sure you understand what each variable means); § Compute descriptive statistics and check for coding errors, recode variables if necessary, pay attention to missing values, identify unusual observations, etc. ; § Develop clear research questions, formulate an analysis plan, and then use available software to answer your research questions; § Carefully study the results and interpret the findings in light of your research questions;

Implementing Marketing Analytics Response models in the decision loop Marketing actions (inputs) Product design, Price, Advertising, Selling effort, etc. Competitive actions Observations (outputs) Awareness Preferences Sales Response Model Environmental Conditions Control, Adaptation Objectives Evaluation

Implementing Marketing Analytics A simple (linear) response model Actual and predicted sales as a function of advertising spending 13400000 12900000 Sales 12400000 11900000 11400000 10900000 10400000 700000 800000 900000 1000000 1100000 1200000 Advertising spending Predicted sales Actual sales 1300000 1400000 1500000

Implementing Marketing Analytics A nonlinear response model

Implementing Marketing Analytics The profit equation

Implementing Marketing Analytics STP – Segmentation, Targeting, Positioning All consumers in the market Marketing mix Product Price Communication Target marketing and positioning Target market segment(s) Distribution Marketing strategies of competitors

Implementing Marketing Analytics Market segmentation Discriminant analysis Response Who’s this? Segment B B 2 Cluster analysis A 2 A 1 B 1 Segment A Who’s this? x 1 x 2 marketing variable

Implementing Marketing Analytics Positioning § What are the central dimensions that underlie customers’ perceptions of brands in the product class? § How do customers view our brand on these dimensions? § How do customers view our competitors? § How do perceptions relate to preferences?

Implementing Marketing Analytics Positioning map with perceptions and preferences Chewy R 2 I (50. 2%) R 1 Chlormint Cooling Effect Mint-O-Fresh Exciting Flavours Fresh Mentos Long Lasting Hard Mahalacto R 3 II (26. 5%) Nutrine

Implementing Marketing Analytics The company’s profit chain Choice models Conjoint analysis Customer value Customer satisfaction Customer loyalty Analyzing and managing customer satisfaction Company profitability CLV

Implementing Marketing Analytics The digital revolution § a lot of unstructured data is available in the online world and marketers can extract useful information from these online conversations by their customers; □ text analysis § digital marketing provides many new opportunities for interacting with customers and exploiting the traces of these interactions □ search analytics