Forrester webinar 20141210

www.vistex.com

Real World Analytics with Big Data:

December 10th 2014

Trends, Best Practices and Insights

Proprietary and confidential. All rights reserved.

Holger Kisker Vice President Research DirectorForrester Research

Presenters

Rob FordDirector of AnalyticsVistex Inc.


Microsoft product manager The past 10 years And now…

DATA DON DRAPER

+

Making Use of Big Data for Business Decisions


AVAILABILITYThere are big

technical barriers to overcome to integrate go-to-market data.

TIMELINESSYou don’t always

have the right data at your fingertips right now to make better decisions.

INSIGHTIn this age of the customer it’s a

challenge to develop analytics

that actually provide insight.

Getting started

2014 VISTEX 5PROPRIETARY AND CONFIDENTIAL

Big Data is gushing

From many sources

Structured Text: data stored in a schema, relational databases, XML, delimited files, XLSUnstructured Text: Free text, emails, documents, Twitter, blogs, LinkedIn, FacebookBinary: Maps, Images, video, voice

From many systems

• ERP • eCommerce • CRM • POS • Web • Email • Excel • Customer Service • Sales • Claims • Planning • MRP • Marketing • Finance • Social Media • Web Analytics • VOC • Data Warehouse • Mobile


Organization of data is foundational

Sales

People

Incentives

Contracts

Orders

Satisfaction

Programs

Geography

Channels


Organization of data is foundational

Sales

People

Incentives

Contracts

Orders

Satisfaction

Programs

Geography

Channels

email

zip

group

ID

click

addr.

time

entity


Descriptive StatisticsAnalysis (why it

happened)

Reporting (what

happened)

BehaviorWho are my best customers?What are they most likely to purchase?

Com

plex

ity

Low

High

HighValue to Business

Analytics available for real world applications


Regression Analysis

Descriptive Statistics

Forecast (what might

happen)Monitor (what’s

happening now)

Analysis (why it

happened)

Reporting (what

happened)

QuantityHow much inventory to carry?How many Partners do we need?What will Sales finish at this year?


Com

plex

ity

Low

High




Regression Analysis


Cluster AnalysisPredict (what’s likely to happen)Forecast

(what might


happening now)

Analysis (why it

happened)

Reporting (what

happened)



Com

plex

ity

Low

High




Simulation

Regression Analysis


Cluster Analysis

Prescribe(what

actions should be

taken)Predict (what’s likely to happen)Forecast

(what might


happening now)

Analysis (why it

happened)

Reporting (what

happened)



OptimalWhat is the impact and lift on sales incentives?Potential outcomes based on complex interactions

Com

plex

ity

Low

High




Simulation

Regression Analysis


Cluster Analysis



OptimalWhat is the impact and lift on sales incentives?What are the financial outcomes based on complex interactions?

Low

High


Analytics available for real world applications Co

mpl

exit

y


Simulation

Regression Analysis


Cluster Analysis



OptimalWhat is the impact and lift on sales incentives?What are the financial outcomes based on complex interactions?

Low

High


Analytics available for real world applications O

perational Strategic

Com

plex

ity

Tactical


How do I assesses the value of my customers?

What it’s called: What it is: What it tells you:

Revenue MetaScore (MVS)

Customer lifetime value The best predictor of which incentives impact general business performance

Recency Value Score (RVS)

Index of which customers purchased most recently

The best predictor of future churn rate

Frequency Value Score (AVS)

Index of which customers most frequently purchase your product, service or brand

A good predictor of new customer growth

Purchasing Value Score (PVS)

Index of which customers purchased the most

The best predictor of overall revenue growth


Discover, explore, and combine multiple data

sources.Assess, visualize,

analyze and ask questions of your data.

Recommend quickly, share broadly and access

insights as-needed.Optimize go-to-market

decisions by learning from learning historical results.

Assess

RecommendOptimize

DiscoverData

Intuitively discover patterns and optimize results


Am I giving incentives to the right customers? Revenue contribution of higher vs. lower margin products.Are certain customers buying only lower margin products?What prices should I set for list and bidding?


ViZi Demo – Revenue Tier Heat Map

Research question: Am I giving incentives to the right customers?KPI: Revenue Tier Achieved | Incentive Tier PaidAnomalies defined as lower revenue, higher rebate compared to otherVisualization: Matched Control Heat Map


ViZi Demo – Incentive > Margin Correlation

Research question: Revenue contribution of higher margin products (low volume) vs. lower margin products (high volume). KPI: Expected Margin | Achieved MarginAnomalies defined as revenue at risk from achieving at or below breakeven.Visualization plan: Quadrant Analysis


ViZi Demo – List price elasticity

Research question: What are the optimal list prices to support my Go-to-Market strategy?KPI: Price Elasticity| Pocket PriceAnomalies defined as unprofitable customers with higher cost-to-serve.Visualization plan: Dynamic Price Waterfall


ViZi Demo – Bid price elasticity

Research question: Are certain customers buying only lower margin products?KPI: List Price | Pocket PriceAnomalies defined as unprofitable customers with higher cost-to-serve.Visualization plan: Dynamic Price Waterfall


ViZi Demo – Dynamic WaterfallResearch question: Are certain customers

buying only lower margin products?KPI: List Price | Pocket PriceAnomalies defined as unprofitable customers with higher cost-to-serve.Visualization plan: Dynamic Price Waterfall


AVAILABILITYAnalytics

Available for Real World

Applications

TIMELINESSThe Value Is in

Getting the Right Data, Now

INSIGHTStrategic

Analytics for Go-To-Market Success

Keys to remember

ANSWERING THE BIG

QUESTIONS

FINDING REAL

WORLD VALUE IN THE HYPE

THE VISTEX SOLUTION

www.vistex.com

Rob FordDirector of [email protected]

Holger KiskerVice President Research [email protected]

Forrester webinar 20141210

Data & Analytics

Transcript of Forrester webinar 20141210