Power Up Your Competitive Price Intelligence With Web Data
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The document discusses the impact of web data on competitive price intelligence, highlighting how transparency has changed in the supply chain. It outlines various use cases for extracting competitive pricing data from the web and emphasizes the importance of data accuracy. The presenters advocate for leveraging web data to optimize pricing strategies and enhance market intelligence across different industries.
Power Up Your Competitive Price Intelligence With Web Data
- 1. Power Up Your Competitive Price Intelligence with Web Data Presenters: Vincent Sgro, Chief Technical Officer, Connotate Christian Giarretta, VP of Sales Engineering, Connotate Moderator: Jeffrey Sacks, Chief Marketing Officer, Connotate Date: May 22, 2013
- 2. Presenters 2 Vincent Sgro Chief Technology Officer Chris Giarretta VP of Sales Engineering
- 3. 3 Transform Web Data into High-Value Assets Some of Our Many Use Cases: Competitive intelligence News aggregation Background check Price optimization Investment research Online ad usage reports Market research Regulatory updates Sales intelligence Business risk assessment Data directories Aggregate construction bids Supply chain monitoring Brand monitoring Voice of the Customer Social media monitoring
- 4. The Web Turned Pricing Upside Down…Exposing Product Data at All Stages in the Product Lifecycle 4 Retail sites Manufacturers’ sites YouTube reviews Product review sites Social media sites eTail sites Auction sites Brand/product aggregator sites Facebook “likes” Distributors’ sites Twitter
- 5. 5 How Does This Affect You?
- 6. Manufacturer Distributor Retailer <<< pricing hidden >>> Before: Limited Price Transparency • Consumers had limited access to real time price differences between competing retailers 6 • Supply chain hid pricing from consumer Retailer 1 Price Retailer 2 Price Retailer 3 Price
- 7. • The Web explodes the supply chain: • The Web, smart phones and Social Media inform consumers of competitor’s prices in real time After: Unprecedented Price Transparency 7 Manufacturer’s price Wholesaler’s price Distributor’s price Retailer 1 price Retailer 2 price Retailer 3 price
- 8. 8 How Should You Respond?
- 9. Use the Web! Extract Competitive Price Intelligence 9 Retail sites Manufacturers’ sites YouTube reviews Product review sites Social media sites eTail sites Auction sites Brand/product aggregator sites Facebook “likes” Distributors’ sites Twitter
- 10. Know at Least as Much as Your Customers! 10 Retail sites Online news sites YouTube reviews Product review sites Social media sites eTail sites Auction sites Brand/product aggregator sites Facebook “likes” Google alerts Twitter
- 11. …And Turn Web Data into Price Intelligence 11 Gain visibility Fine-tune strategy Regain control Data Results: Retailers: • Competitors’ prices on high-margin items • Increase market share 10% Big Box Manufacturers: • Retailers’ prices and discounts • Retain channels repeat orders Electronics: • Going prices for used devices before and after refurbishing • Boost “foot traffic” + sales 5% by expanding sales of software for used devices
- 12. 12 Workflow of Web Data in Competitive Price Intelligence
- 13. Workflow Overview 13 Position Name Score Through 1t Garcia -6 18 1t Jacobson -6 18 6t Hanson -5 18 6t Stricker -5 18 10t Bradley -4 18 Option 2: You control the workflow. Access Web page Transform Data Feed BI Apps Option 1: Outsource the process. Pay 3rd party to collect/analyze data You receive reports
- 14. 14 In Order to Use Web Data, You Need to Find It, Filter It and Format It…
- 15. Accuracy is Important in Web Data Extraction “Business intelligence projects often fail due to dirty data” “Organizations over estimate the quality of their data and the cost of data errors” 15
- 16. Accuracy is Key to Actionable Insights • Assuring quality data requires investment up front but it is well worth it • Automation improves data quality to achieve the optimum cost tradeoff 16 Cost of bad data = cost of fixing errors + cost of faulty decisions Clean data + context Information Information + analysis Actionable insights
- 17. • Connotate has tackled the problem in a new way, simplifying the process and making it resilient to change. • Transforming Web page content into computer-friendly data is much more difficult than it first appears. Accuracy is Not an Easy Problem to Solve 17
- 18. Polling Question: Web Data Collection Are you currently collecting data from the Web? Yes – we are doing this using an automated process Yes – we are collecting Web data using a manual process Yes – we are using BOTH manual and automated approaches No – we are not collecting Web data
- 19. 19 Competitive Price Intelligence Use Cases
- 20. Retail Auto Parts • Challenge/Opportunity • Obtain more timely visibility into competitors’ pricing to support dynamic pricing – particularly on high-margin “convenience” items • Reduce dependency on expensive pricing catalogs (updated weekly) • Solution • Monitor competitors’ websites daily to obtain timely pricing intelligence at both the national and local levels • Business Benefit • Increased market share 10%, moving up in national rankings – optimizing pricing by making decisions based on timely data • Reduce cash outlay for pricing catalog subscriptions 20
- 21. Auto Parts: Extract Data From Web Pages 21 Extract: • Product • Item # • Availability • Price • Category Ignore: • Ads, etc.
- 22. Auto Parts: Web Data Transformed 22 Clean, clear, consumable data
- 23. Appliance Manufacturer (Supplier to Big Box Retailer) • Challenge/Opportunity • Obtain a “360 view” of products through the entire distribution chain to optimize product positioning, pricing and branding strategy • Solution • Use automation to extract data from competitors websites daily to gain visibility • Business Benefit • Retaining channels, ensuring repeat orders with a well-informed product enhancement strategy based on continual access to pricing and product reviews at the retail level 23
- 24. Appliance Manufacturer: Extract Data and Reviews from Web Pages 24 Extract: • Product ID • Specs • Price • Ratings • Comments Ignore: • Ads, etc.
- 25. PRODUCT ID Rating Comment EAB7900SKSK09 5 The Yankees’ Mariano Rivera, revered as one of baseball’s gentlemen and perhaps its greatest closer, is expected to announce that this season will be his last… EA27903SKSK77 2 Marian Gaborik scored a power-play goal against the Islanders in overtime to extend the Rangers’ winning streak to four games… INT79034777009 4 It’s not enough to retire. Now players like Mariano Rivera are announcing that they will announce their retirements… PRODUCT ID CATEGORY SIZE PRIC E EAB7900SKSK09 Refrigerator 6 cu ft 2099 EA27903SKSK77 Refrigerator 4 cu ft 289 INT7903458SK89 Gas Range 24” 499 INT79034777009 Gas Range 24” 638 IQ666903EFFFFA Gas Range 24” 310 Accuracy, Speed, Automated Delivery 25 Clean data, delivered to the right place in the right format: • Product IDs, specs prices to spreadsheets • Product reviews to sentiment analysis applications
- 26. Appliance Manufacturer: Web Data Transformed 26 • Product • Product ID • Price • Specs • Product • Product ID • Rating • Comments
- 27. Buying and Selling Refurbished Electronics • Challenge/Opportunity • Expand activity in the growing market for used tablets/smartphones • Expand sales of apps and games for used devices • Solution • Extract prices for used devices from auction sites; extract prices from Gazelle, and similar sites to determine prices for refurbished items • Business Benefit • Increase foot traffic and boost revenue by 5% by expanding operations into the growing market for used/refurbished devices (and sales of apps and games for those devices) 27
- 28. Electronics: Extract Data from Web Pages 28 Offer price for un-refurbished Selling price for refurbished item
- 29. Electronics: Web Data Transformed 29 Automatically merges data from two different websites in a “mashup” in one spreadsheet to facilitate comparison and analysis
- 30. Polling Question: Competitive Intelligence and Pricing Strategy Do you support a competitive intelligence or pricing strategy function in-house? Yes – our business intelligence (BI) or Pricing team uses Excel spreadsheets to support our CI/pricing strategy. Yes – we use BI tools in-house (Microstrategy, Oracle Endeca, SAP, IBM Cognos, etc.) to support our CI/pricing strategy. No – we outsource our CI/pricing function to an outside vendor. No – we have not implemented a pricing strategy Other ____________________________________
- 32. Manual versus Automated Approaches 32 Your Data Needs To Automate or Not? High-volume data monitoring Automate Variety of sources Automate Frequent updates and/or monitoring Automate Need for data post-processing Automate Small amount of data required just a few times a year from very simple sites A manual approach may be adequate One-time feed of very specific data Purchase data from 3rd party Product matching applications where unique identifiers are not available We can offer a solution which incorporates crowdsourcing or outsourcing
- 33. 33 Scope Your Project: 5 Steps
- 34. Scoping Your Project: 5 Steps to Success 1. Clarify what you want to do with the data 2. Look at what’s happening manually today – find out how users are accessing the Web – these are targets for automation 3. Identify the sources you need 4. Narrow your scope….you may not need“everything” 5. Anticipate future requirements 34
- 35. Scoping: Use Cases Retail Auto Parts • Customer wanted to collect “everything” • In this case, that was needed but we worked with them to devise a system for automated product matching Appliance Manufacturing • Customer wanted to collect “everything” from many, many sites • We refined the scope of the project to collect a sample size that would meet their needs and be faster and less expensive to implement Used Electronics • Customer scoped a complex database model of lookup tables; we advised a different approach with much less overhead • We steered them toward an efficient method for extracting metadata 35
- 36. Polling Question: The Value of Automated Web Data Collection Do you believe using automated Web data extraction to gather competitive intelligence could add value to your business? Yes – we are doing this now Yes – we are planning a project in the near future No – not at this time I need more information before deciding
- 37. Here’s What Success Looks Like… Increase market share 10% overtake next competitor by optimizing prices Appliance manufacturers ensure repeat orders from Big Box Retailers Retailers expand their presence in the lucrative market for used devices Electronic game retailers achieve 5% increase in software sales revenue 37 … Connotate’s experts are ready to take you there
- 38. Q & A Connotate will email a link to this presentation as well as a copy of the slides to you within 2 business days. If you have an immediate need and would like us to contact you about a forthcoming project, please check the appropriate box in the last polling question or call (+1) 732-296-8844. For more information, visit www.connotate.com or www.connotate.co.uk 38