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CRM Data Myths

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Too often data myths lead to inefficient processes in CRM, broken systems and/or paralysis analysis. You don’t need to wield the hammer of Thor to make progress with your data management strategy, you just have to separate fact from fable.

On this recorded webinar, Donato Diorio (@idonato) and Michael Farrington (@michaelforce), two experts in CRM and marketing automation technology, dispel several common data myths providing tangible and actionable advice to ensure good fortune for all who rely on your data.

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CRM Data Myths

  1. 1. Dispelling CRM Data Myths Donato Diorio Founder & CEO Broadlook Technologies www.broadlook.com #DataMyths Michael Farrington Chief Product Officer RingLead www.ringlead.com
  2. 2. Key trends in CRM Metrics/ Dashboards Social Cloud Big data & sales intelligence #DataMyths Mobile Analytics Collaborative selling Empowered Users
  3. 3. The Foundation: Good CRM Data Without… Clean Protect #DataMyths Enhance Enhanc e
  4. 4. The Foundation: Good CRM Data Without… Clean Protect Without performing a comprehensive data cleanse, the foundation is weak #DataMyths Poor foundation Enhance Enhanc e
  5. 5. The Foundation: Good CRM Data Without a protection Without… strategy, your data will continually decay Clean Decaying data Protect #DataMyths Enhance Enhanc e
  6. 6. The Foundation: Good CRM Data Without enhancing your existing data you limit your “data potential” Without… Clean Limited potential Protect #DataMyths Enhance Enhanc e
  7. 7. MYTH It’s ok to delete data #DataMyths
  8. 8. Never delete CRM data - Score it Instead! Notes: 11/21/13: 06/15/13: 04/10/13: 03/19/11: Donato is the decision maker for CRM Add ons Dan went to Kansas State, played football April is Donato’s assistant Matt Smith is the new Doctor, Donato is Dr. Who fan #DataMyths
  9. 9. Scoring Data: Focus on Good Data Notes: 11/21/13: 06/15/13: 04/10/13: 03/19/11: Donato is the decision maker for CRM Add ons Dan went to Kansas State, played football April is Donato’s assistant Matt Smith is the new Doctor, Donato is Dr. Who fan #DataMyths
  10. 10. What can we learn/derive from the existing data? • • • • • • • • • Domain is broadlook.com Email pattern in first-initial(.)last-name April reports to Donato On broadlook.com, there are 15 additional contacts Notes on Donato are 1 month old Notes on April are 8 months old Natalie is no longer at the company “The Doctor” is a fictional character Natalie is now a VP at another company - and an additional prospect! #DataMyths
  11. 11. MYTH Using the stick works: make all fields required! #DataMyths
  12. 12. Using the stick works • Determine carrot and/or stick on field basis, not object • Educate users on the importance of everything you ask of them (focus on selfish reasons) • Don’t ask what they don’t know #DataMyths
  13. 13. MYTH Training works to enforce data standards #DataMyths
  14. 14. #DataMyths
  15. 15. Enforcing Data Standards is Optimal #DataMyths
  16. 16. MYTH My Data is Fairly Complete #DataMyths
  17. 17. My Data is Fairly Complete • Superstition or fact? Find out! #DataMyths
  18. 18. My Data is Fairly Complete #DataMyths
  19. 19. MYTH Buy as much data as you can, all at once (because it’s cheaper) #DataMyths
  20. 20. Data decay happens • Change in title, promotion • Change of department • Change in working location • Change of area code • Change of phone number • Change of email format • Add mobile phone number • Merger or acquisition #DataMyths
  21. 21. #DataMyths
  22. 22. MYTH Bad Data is IT’s Problem #DataMyths
  23. 23. Bad Data is IT’s Problem • He who reporteth upon it... • Treat it like a project • Choose Data Quality applications that don’t require a PhD in Computer Physiology #DataMyths
  24. 24. MYTH The company’s name is more important than the website address #DataMyths
  25. 25. Company Based Changes Decade Multi year Year Contact based Event & Activity Based Quarter Month Day Static Data types Acquisition method URL Database merging + algorithm Update strategy #DataMyths Hour Dynamic Corp Name City State Address Zip Phone Competitors Editorial & Aggregation Revenue Employees Products Services Financials Editorial + SEC spidering Static, compiled and online databases Names Titles Emails address Phone Biographies Social Network Links Real time content spidering News Email content Blogs Net links social networks newsgroups Tweet Check-In’s Proximity Website visits Email reads Semantic monitoring services Real time API’s Real time
  26. 26. MYTH I know how to search for duplicates #DataMyths
  27. 27. I know how to search for duplicates • It gets messy • Users may not have access • Even if you do, is that a good use of your (user’s) time? #DataMyths
  28. 28. MYTH My vendor’s data is better than mine (they are the specialists right?) #DataMyths
  29. 29. Data industry processes •Buy data from multiple sources •Refresh top companies with editors •6 month cycle (top 10K companies) •6-12 month (next 40K companies) •24 month cycle on the next 2 million •Nothing past the top 2 million •Add social data (good for top 10%) •Add news feeds (good for top 5%) •Mob source #DataMyths
  30. 30. Buying data...why, how and gotchas How recent is the list as whole? How quickly was the list produced? Different from record freshness. Contact data degrades 3% per month (5% in a stressed economy). A list of 1000 records can be built over 60 days. In the case below, the first 500 records are 8 weeks old (5.68% inaccurate) upon list delivery. 96.8% #DataMyths
  31. 31. Buying data...why, how and gotchas 86.5% #DataMyths 59.5%
  32. 32. Your data vs. your vendor’s • Your data is less complete • Your data has a better competitive advantage • Use their data to fill in your data #DataMyths
  33. 33. MYTH My data is awesome! #DataMyths
  34. 34. CRM Data Quality Points 4 3 2 1 Fresh <30 days <60 days <90 days <180 days Accurate 95.00% 80% + 70% + 60% + Multi-venue All available Basic + 2 social Basic + 1 social Basic (email+phone) Built fast <14 days < 60 days < 90 days < 180 days Normalized Enforced Plan + culture Has plan no Scored Custom rules Accessible rules white box scoring black box scoring Factors Total data quality score: #DataMyths Your score
  35. 35. CRM Competitive Advantage Points 4 3 2 1 target by self description hand built keywords SIC code built on-demand mashed from many sources pulled from larger sample Complete 95%+ 80.0% 60.0% 40.0% Exclusive no competitors limited access anyone can buy access free Sources transparent sources known sources available By a person Marketing automation email Factors Targeted Custom Transparent Verified Total competitive advantage score: #DataMyths Your score
  36. 36. Where is your CRM data? Competitive Advantage 24 12 0 12 Data Quality #DataMyths 24
  37. 37. What is your data potential? Qualitative / Event-Driven Qualitative Cyclic Quantitative / Cyclic Quantitative/ commodity Competitive Advantage Quadrant Key 24 Influence Relationship m o a 12 ng ti ke ar ut a on ti CRM+ 90 days CRM+ 180 m CRM+ days 360 days Cold Call 0 new CRM lead Warm call 12 Data Quality #DataMyths 24
  38. 38. MYTH Preventing Duplicate Records Based on Email is Sufficient #DataMyths
  39. 39. Preventing Duplicate Records Based on Email is Sufficient ● No. Not even for sending emails. ● Email addresses are not social security numbers ● True story: I had four email addresses at one company #DataMyths
  40. 40. MYTH My sales team lets me know what they need #DataMyths
  41. 41. The Evolution of Sales Desire I want...More data (lists) I want... Better selection (databases) I want... More contacts per company (zoom) I want... Fresher contacts(Jigsaw) I want... More information (LinkedIn) I want... More knowledge (many sources) I want... More process (crm) I want... Sustainable process Data Information #DataMyths Knowledge Process
  42. 42. Questions? If you have questions or would like to begin a free trial, please contact us! Join the RingLead Usergroup +1-888-240-8088 sales@ringlead.com www.RingLead.com RingLead.com/LinkedIn Follow us on Twitter @ringlead @iDonato @michaelforce Become a Fan on Facebook RingLead.com/Facebook Subscribe to our YouTube Channel RingLead.com/YouTube #DataMyths

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