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Business Situation: The client, a leading hair care manufacturer wanted to identify drivers of brand preference for the category which would aid them in designing the right marketing strategy & related collateral for strengthening market share for their existing brand. Analytical Framework: Design a Structural Equation Model (SEM) to identify key equity themes & their hierarchy in terms of importance in driving purchase for the category, and identify the best pathway to improve the brand’s equity in consumer’s mind. The Result: The following recommendations were made and implemented by the business: Leverage Brand’s strength on the “health” dimension – this goes in line with brand’s equity pyramid “Ingredient” is one of the key category drivers on which the brand is performing very well – strengthen communication strategy to capture this Even though health benefit is key, consumer’s eventually desire the beauty aspect – Redesign communication strategy to convey this as the end benefit Currently “beauty” dimension is weak – build credibility on that with consistent communication Analytics in Action Re-design Product Communication Strategies in line with Consumer Preferences Client: Leading Hair Care Manufacturer Marketing strategy on the core “Health” benefit & it’s eventual impact on making oneself attractive is the “Key” Overall Brand Equity Feel Confident & Energised 15% Trust 10% Effective 8% Expert Brand 3% Leaves hair soft ,smooth and shiny 11% Hair Health 10% Color Protection 1% Conditioning 3% Ingredients 11% Brand for me 6% Attractiveness 10% Beautiful and Empowered 1% Leading Brand 2% Fragrance 5% Experience 1% For men and women 0.3% Dandruff and Scalp issues 4% 0.60 0.37 0.83 0.21 0.90 0.63 0.30 0.09 0.29 0.15 0.80 Strong relationship Moderately strong relationship Weak relationship 0.78 0.19 0.90 0.90 0.90 0.90 0.90 0.16

Analytics in Action - How Marketelligent helped a Hair Care Manufacturer Re-design its Product Communication Strategies

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Page 1: Analytics in Action - How Marketelligent helped a Hair Care Manufacturer Re-design its Product Communication Strategies

Business Situation: The client, a leading hair care manufacturer wanted to identify drivers of brand preference for the category which would aid them in designing the right marketing strategy & related collateral for strengthening market share for their existing brand.

Analytical Framework: Design a Structural Equation Model (SEM) to identify key equity themes & their hierarchy in terms of importance in driving purchase for the category, and identify the best pathway to improve the brand’s equity in consumer’s mind.

The Result: The following recommendations were made and implemented by the business:

₋ Leverage Brand’s strength on the “health” dimension – this goes in line with brand’s equity pyramid ₋ “Ingredient” is one of the key category drivers on which the brand is performing very well – strengthen communication strategy to

capture this ₋ Even though health benefit is key, consumer’s eventually desire the beauty aspect – Redesign communication strategy to convey this

as the end benefit ₋ Currently “beauty” dimension is weak – build credibility on that with consistent communication

Analytics in Action Re-design Product Communication Strategies in line with Consumer Preferences

Client: Leading Hair Care Manufacturer

Marketing strategy on the core “Health” benefit & it’s eventual impact on making oneself attractive is the “Key”

Overall Brand Equity

Feel Confident & Energised

15%

Trust 10%

Effective 8%

Expert Brand 3%

Leaves hair soft ,smooth

and shiny 11%

Hair Health 10%

Color Protection

1%

Conditioning 3%

Ingredients 11%

Brand for me 6%

Attractiveness 10%

Beautiful and Empowered

1%

Leading Brand 2%

Fragrance 5%

Experience 1%

For men and women

0.3%

Dandruff and Scalp issues

4%

0.60

0.37

0.83

0.21

0.90

0.63

0.30

0.09 0.29 0.15

0.80

Strong relationship

Moderately strong relationship

Weak relationship

0.78 0.19 0.90 0.90 0.90

0.90

0.90

0.16

Page 2: Analytics in Action - How Marketelligent helped a Hair Care Manufacturer Re-design its Product Communication Strategies

MANAGEMENT TEAM GLOBAL EXPERIENCE.

PROVEN RESULTS.

Roy K. Cherian CEO Roy has over 20 years of rich experience in marketing, advertising and media in organizations like Nestle India, United Breweries, FCB and Feedback Ventures. He holds an MBA from IIM Ahmedabad.

Anunay Gupta, PhD COO & Head of Analytics Anunay has over 15 years of experience, with a significant portion focused on Analytics in Consumer Finance. In his last assignment at Citigroup, he was responsible for all Decision Management functions for the US Cards portfolio of Citigroup, covering approx $150B in assets. Anunay holds an MBA in Finance from NYU Stern School of Business.

Buck Chintamani EVP, Strategic Initiatives & Business Development Buck has extensive experience working with global clients across sectors. He was an early employee at Infosys, a founding team member at supply-chain software startup - Yantra, and part of the management team at RFID sector startup - Reva. Most recently, he was the Vice-President for Service Partner Strategy and Programs at product lifecycle management software company, PTC. Buck has an MBA from IIM Ahmedabad.

Kakul Paul Business Head, CPG Kakul has over 8 years of experience within the CPG industry. She was previously part of the Analytics practice as WNS, leading analytic initiatives for top Fortune 50 clients globally. She has extensive experience in what drives Consumer purchase behavior, market mix modeling, pricing & promotion analytics, etc. Kakul has an MBA from IIM Ahmedabad.

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CONTACT www.marketelligent.com

Industry Business Focus Tools and Techniques

Consumer Finance Investment Optimization SAS, SPSS, R, VBA

Credit Cards Revenue Maximization Cluster analysis

Loans and Mortgages Cost and Process Efficiencies Factor analysis

Retail Banking & Insurance Forecasting Structural Equation Modeling

Wealth Management Predictive Modeling Conjoint analysis

Consumer Goods and Retail Risk Management Perceptual maps

CPG & Retail Pricing Optimization Neural Networks

Consumer Durables Customer Segmentation Chaid / CART

Manufacturing and Supply Chain Drivers Analysis Genetic Algorithms

High Tech OEM’s Supply Chain Management Support Vector Machines

Automotive Sentiment Analysis

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