Competitive Analytics

Competitive Analytics Utilize data to help analyze future scenarios to make more accurate assumptions Ed Allison Compelligence, Inc.

Ed Allison Education: Computer & Management Science US Army: Captain Career Cisco Systems Symbol Technologies Juniper Networks Polycom Compelligence Speaker

Rules of the road Information Compelligence

Compelligence Who we are Intelligent Competitive Sales Strategies Fact Based Messaging Real Time Feedback Win / Loss Analysis

Competitive Analytics Utilize data to help analyze future scenarios to make more accurate assumptions Planning and Forecasting is often based on quantitative analysis comparing scenarios based on assumptions of business forces in your future environment. The largest unknown is the future. What if we could use data to help analyze those future scenarios to make more accurate assumptions. Using technology we can analyze trends in the market place, track sales feedback via win/loss analysis and compare offers in a more analytical manner to eliminate uncertainty for planning.

Analytics Where did it begin?

Is this technique becoming more popular?

Competitive Intelligence is becoming a Customer Exercise

Definition: Analytics The discovery and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. Analytics often favors data visualization to communicate insight. -wikipedia.com

What is an Analytical Competitor Extensive use of data, statistical and quantitative analysis, exploratory and predictive models and factbased management to drive decisions and actions.

What is an Analytical Competitor

Use of Analytics: What matters The best intelligence in the world is of little use if it is not presented in a manner that makes it credible, compelling and relevant for senior executives. - Ken Sawka Outward Insights (now Fuld)

Analytics: Organizational-wide Analytics cannot be utilized only by executives but must be used by all teams regardless if you are designing and building offers, selling them, or leading the organization that does. - Edward Allison Compelligence, Inc.

Types of Competitive Deliverables Early Warning Systems (Most likely Course of Action Analysis) Sentiment Analysis / Reputation Analysis Trend / Timeline / Event Analysis Product / Solution Analysis (Feature / Functionality Analysis) Win / Loss Analysis Financial Analysis / Financial Forensics Analysis SWOT Analysis SEO Analysis Strategic Threat Report Feature Velocity Analysis Market Share Analysis Customer Persona Analysis more

Examples of Competitive Analytical Reports

What do we all have in common?

What do we all have in coming? Strategic (Vision) Annual Operating Plan ($) Marketing Plans Product / Solution Planning Account Planning

Keys to Success for a Competitive Intelligence Program Executive Sponsorship Start with Sales Cultural Support Centralized Management Distributed Participation & Utilization Metris Driven

Competitive Analytical Reports: Executives

Example: Competitor Threat Dashboard Access and Reporting (More) Analytics

Example: Competitor Threat Dashboard

Competitive Analysis Analytics FAROUT Methodology

Competitive Analysis Analytics FAROUT Methodology Future Oriented Accurate Resource Efficient Objective Useful Timely

Product and Solution Planning Discovery 1 Scoping 2 Business Analysis 3 Development 4 Testing & Validation 5 Launch 6 Post Launch Analysis

Competitive Analytics for Discovery Discovery 1 Scoping 2 Business Analysis 3 Development 4 Testing Development & Validation 5 Testing Launch & Validation Early Warning Systems Trend / Timeline / Event Analysis Win / Loss Analysis Product Analytics SEO Analysis Feature Velocity Analysis Market Share Analysis Customer Persona Analysis many more 6 Post Launch Analysis

Timeline Analysis / Trend Analysis

Timeline Analysis / Trend Analysis Who: Product Management, Product Marketing What: Concept Commit, Product Proposal Meetings When: Phase 1 of NPI Process Where (How): Slides Why: Influence & Build Consensus Problem: Intuition, Bias, Not Metrics Based

Going beyond observation: Early Warning Analysis Event Event Event Event Event Environmental Monitoring System Trend 1 Trend 2 Trend 3 Report / Dashboard

Real World Intelligence: Fall of the Soviet Union

Competitive Analytics: A Practical Application of Prediction

Trend Analysis Systems

Tools Examples

Compelligence: Distributed Intelligent Monitoring & Logging

Win / Loss Analysis

Win Loss Analysis Who: Sales, Product Management, Product Marketing What: Concept Commit, Post Launch Analysis When: Phase 1 & Phase 6 of NPI Process Where (How): Dashboards, Excel Files, Slides Why: Influence & Build Consensus Problem: Usually not analytics

Win Loss Analysis In this book Rick Marcet reveals a new knowledge model that taps into one of the most under utilized sources of business and competitive intelligence your sales staff.

Typical Win / Loss Report

Win Loss Analysis Example 12,000 10,000 8,000 6,000 4,000 2,000 Why Polycom Wins Government (Non USA) Transportation To be Determined Telecommunication equipment/ services Telecom Technology Technology Systems Integrator State & Local Government (USA & No Service Provider Pharmaceuticals Petroleum Petroleum Other Manufacturing IT Consulting/Services Information Technology - Price Quality/Reliability Relationship (Channel) Relationship (Polycom) Technology Hospitals Higher Educ (University/College)

Tools Example: Primary Intelligence

Transaction Data & Intelligent Win / Loss Analysis to build a Dataset

Win / Loss is a component of Analytics Often an organizational issue, not an analyst issue http://www.crmswitch.com/crm-industry/usa-crm-market-share-2013/

. What if you were RIM?

Competitive Analytics for Discovery Discovery 1 Scoping 2 Business Analysis 3 Development Early Warning Systems Trend / Timeline / Event Analysis Win / Loss Analysis SEO Analysis Product & Feature Velocity Analysis Market Share Analysis Customer Persona Analysis more 4 Development 5 Testing & Validation 6 Post Launch Analysis

Product & Feature Velocity Analysis

Typical Tools (Excel) are Descriptive

Dynamic Objective Product Analysis Excel s Conditional Formatting can be useful

Product Analytics to Help Sales Win

Analytics enables Silver Bullets for Sales

Analytics is required to face a new changing Competitive Landscape

Questions