Marketelligent Capabilities and

Offerings for Sales Analytics

Epicentre for share loss for a leading brand was the Private channel within the South region

Sales tracker for enabling a real time understanding ofthe business performance to help identify outages in atimely manner and ensure immediate course-correctionmeasures.

Below is an example of how a leading alco-bevmanufacture in India is tracking sales performance forall key states by regions/channels/outlets. The reporthelped the client identify epicenter of share loss for oneof its leading brand in one of the top salient markets.

Break-up of our brand’s overall 5% share loss in by Regions Break-up of our brand’s 3.2% share loss in South Region by Channels

SKU 1 is driving the share loss in South Region Pvt. channel

• Most of the share loss was coming from their leading SKU in the South region in the Private channel. We also highlighted the top salient outlets that needed to be addressed on priority basis.

• Based on this, the client was able to draft out the counter strategy for the priority outlets.

Benefits to the Business

Sales report & trend analysis

Evaluate growth pillars for the category (regions, sub-categories) based on historic & forecasted growth trend

Sales tracker for enabling a real time understanding ofthe business performance to help identify outages in atimely manner and ensure immediate course-correctionmeasures.

Below is an example of a leading OTC player is lookingat drafting their annual strategic plan for all their corecategories based on historic performance acrossmarkets and forecasted growth.

Sales report & trend analysis across markets

Marketelligent PRISM calculates the incremental saleslift (µ) because of various in-store promotions withoutbuilding a predictive model.

It is a real-time tool that provides continuousmonitoring and evaluation of promotion effectiveness.

Marketelligent PRISM for measuring sales lift from streaming sales data

Framework for continuous monitoring and evaluation of trade and marketing programs

Streaming sales data(Weekly or Monthly)

Sales and Marketing promotion calendar

Sales and Marketing promotion Spends

Weekly trends of promotional activity• Lift• Incremental sales

After activity reports• Total lift• Total incremental sales• ROI

Quarterly Reports• Cross Category / Channel /

Geography summaries

INPUT OUTPUT

Continuous monitoring & evaluation

Learnings fed back for future planning

µ Display

µ Feature

µ Consumer

µ TPR

Decomposed Lift (µ)

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Streaming sales data fed weekly or monthly as is available

Promotion calendar fed into the system periodically

Marketelligent PRISM

Marketelligent PRISM

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Price index vs. competition Volume share

Optimum price corridor

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Simulator for predicting volume share movement based on price changes in the market

Updated price to be entered for

each brand

Simulator predicts the updated volume share

for the brand

Price Corridor to play for maintaining your share vs. competition

Building a predictive model to understand howsensitive our brand’s share is to our brand’s pricing.Based on the predictive model, create a simulatorwhich can be used for identifying:- Optimum price band to operate in given

competitor price changes while minimizing share

low- Price thresholds for our brand beyond which there

is considerable share change- Price threshold with respect to competition

beyond which there is considerable share change

Pricing Simulator

A good demand forecast helps improve sales volume,cash flow and hence the profitability, by optimizinginventory and by minimizing out-of-stock. Besidesconsidering historical data, external factors like

promotion, seasonality, price changes, macro-economic conditions are also considered for moreaccurate forecasts.

Different statistical techniques used for sales forecasting:

Sales Forecasting

Forecasting sales for a leading alco-bev manufacturer

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ARIMA (Autoregressive integrated moving average) Holt-Winters Forecasting

Year on Year Growth Rate model

• Inventory Control• Minimizing Out of Stock• Improving product

freshness & warehouse efficiency

• Maximizing warehouse space utilization

• Capitalizing on peak sales weeks

Benefits to the Business

The SKU Rationalization study evaluated factors suchas overall revenue contribution, growth rates andprofile of customers buying a particular segment.These metrics were compared with overall style groupand color customer preferences YoY, and a comparison

of reactivation behavior of returning customers whoseSKUs were discontinued post 2010 v/s those whoseSKUs were not. We helped the client arrive at astrategy that rationalized 30-40% of SKUs in varioussegments with no risk of a revenue impact.

• Color and style group preferences consistent YoY; safe to rationalize non performing categories• Reactivation levels for discontinued v/s continued SKU customers• Customer sub segments further analysed to exclude any SKUs from rationalization that may impact revenues

Secondary Analysis

• Segmentation of top 80% style groups, 80-98% style groups and bottom 2%

• Cap for top colors in top 80% style

Primary analysis

SKU Rationalization

Trade Promotion Optimization (TPO) uses advancedeconometric modeling techniques to helpmanufacturers refine their trade promotion strategies.The optimizer measures the impact of the varioussales promotions across channels , categories and

helps the sales team reallocate the promotionalspends to maximize the sales lift from promotions.The model below was used to optimize the tradespends of a large CPG company.

5 step framework for optimizing trade budgets

Simulator used to re-allocate trade spends across brands and activities

• The simulator was used by the sales operations team to allocate/ decide promotions across channels and categories

• The simulator could be used to predict the business impact of the various trade promotions

• The simulator could also be used to decide promotional slabs to achieve a desired volume

Benefits to the Business

Trade Promotion Optimization

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Volume decomposed by media and base volumeMagazines are gaining importance in driving incremental sales

Market mix modeling is a predictive modelingtechnique used to understand the impact of variousmarketing vehicles in driving incremental sales. It isthen used to plan future marketing budget allocationby optimizing spends while generating a higher ROI.

The case study below is for a leading manufacturer inthe anti-ageing category. The analysis indicated thatsales loss was because of internal cannibalization andcould have been arrested if the media spends onmagazine was not reduce d

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Baseline sales Magazine incr. sales TV incr. sales Daily incr. sales

Magazine spend TV spend Dailies spend

1.58%

-0.30%

-2.47%

-1.88%

2.78%

-6.23%

-6.51%

-8.00% -6.00% -4.00% -2.00% 0.00% 2.00% 4.00%

Incremental Drivers

-1.18%

Base

Drivers

-5.33%

Cannibalization by new product

There is one point increase in Wtd. distribution

Marginal increase in avg. price

36% Decrease in spends

24% Decrease in spends

42% Increase in spends

Total volume change

Wtd. distribution

Magazine

Brand Y product launch

Base price

Daily

TV

Brand X source of sales decline 2011 vs. 2010

• Brand Y launch has cannibalized Brand X volumes• The decline could have been restricted if the magazine spends was not reduced

Market Mix Modeling

Marketelligent provides data analytics basedconsulting and outsourcing services that help youmake smarter business decisions. The firm is backedby senior professionals with experience acrossConsumer focused industries - Retail Banking,

Consumer Packaged Goods, Retail, Telecom andMedia. We offer an affordable global delivery modelleveraging the best of domain expertise and analyticcapabilities.

Reporting and Dashboard Custom Analysis Modeling

• Sales and Market Share tracking• KPI reporting• Category / Channel Trends• Web based dashboards

• Market Structure Analysis• Meta analysis / Data Integration• Global opportunity mapping

• Marketing Mix Optimization• Trade Spend Optimization• Structural Equation Modeling • Pricing analytics• Sales forecasting

Offerings in CPG Analytics :

MANAGEMENT TEAMGLOBAL EXPERIENCE.

PROVEN RESULTS.

Roy K. CherianCEORoy has over 20 years of rich experience in marketing, advertising and mediain organizations like Nestle India, United Breweries, FCB and FeedbackVentures. He holds an MBA from IIM Ahmedabad.

Anunay Gupta, PhDCOO & Head of AnalyticsAnunay has over 15 years of experience, with a significant portion focusedon Analytics in Consumer Finance. In his last assignment at Citigroup, he wasresponsible for all Decision Management functions for the US Cardsportfolio of Citigroup, covering approx $150B in assets. Anunay holds anMBA in Finance from NYU Stern School of Business.

Greg FerdinandEVP, Business DevelopmentGreg has over 20 years of experience in global marketing, strategic planning,business development and analytics at Dell, Capital One and AT&T. He hassuccessfully developed and embedded analytic-driven programs into avariety of go-to-market, customer and operational functions. Greg holds anMBA from NYU Stern School of Business

Kakul PaulBusiness Head, CPGKakul has over 8 years of experience within the CPG industry. She waspreviously part of the Analytics practice as WNS, leading analytic initiativesfor top Fortune 50 clients globally. She has extensive experience in whatdrives Consumer purchase behavior, market mix modeling, pricing &promotion analytics, etc. Kakul has an MBA from IIM Ahmedabad.

MARKETELLIGENT, INC.80 Broad Street, 5th Floor, New York, NY 10004

1.212.837.7827 (o) 1.208.439.5551 (fax) info@marketelligent.com

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