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#Datafabric
The New Frontier: How to Gain Insight with Interwoven Quality DataWebinar with Jake Dolezal, Mike Franko & Donato Diorio
Data as a Story
✤ Data is an asset
✤ Data tells stories
✤ Humans have used stories as our principle means of communication for thousands of years
#Datafabric
Each system tells a story
✤ CRM tells customer stories
✤ ERP tells enterprise stories
✤ Point-of-sale transactions are vignettes of customer purchases
#Datafabric
Quality matters
Tell the…
✤ Most complete
✤ Most accurate
✤ Most consistent
Story possible#Datafabric
I have great quality data, so now what?
✤ Even with data of the highest quality, it still only tells a small isolated story.
✤ An eye-witness account is biased by its limited point-of-view.
✤ It may be correct, but it is only one perspective
✤ But what about the other interactions that lead to that purchase? What happened? Who did they talk to? What did they see or hear? What influenced them?
✤ Don’t be shortsighted and only see part of the story
#Datafabric
Bringing data together…the old way
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Conventional integration cannot keep up!
#Datafabric
Introducing the Data Fabric…
#Datafabric
Single point of entry for all data
#Datafabric
Data Practice Evolution
#Datafabric
#Datafabric
• Companies solve the problems themselves • Focus on symptoms vs. cause • Every project starts anew • Very little automation • Service costs are astronomical • Over time & budget
The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency. -‐Bill Gates
Data Evolution: Do-it-yourself era
#Datafabric
• Focus is still symptom vs. cause • Product is reviewed more than the
problem (whether is it dedupe, data fill, etc ) • Product fit is the focus • Gaps in the product-‐solution are
ignored • Leads to partial solutions • Less consultative sales process
The problem always looks like a nail when you only have a hammer.
Data Evolution: Product era
Data Evolution: Consultant era
• Consultants are product specialists, process generalists
• Learning on client’s time • Abundance of “try and fix” iterations • Longer process, most expensive • More expensive than doing it in-‐house • Gaps in the product-‐solution are ignored • Failure rate is similar to early CRM
implementations
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Data Evolution: Expert era
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• Experts in product and process • Quicker process • Less expensive than doing it in-‐house • “Try & fix” iterations much less
common • Success is common, break downs
happen when advice is ignored
Data Evolution: Assessment era
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• Data assessment starts the process • Decisions based on data facts vs.
expert hunches • Fewer “try and fix” iterations • Assessment provides better visibility
into solution set required • Fastest time to start and complete
project • Once you assess, ready for expert!
9 lost secrets of Clean Data
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What is Clean Data?
Minimalist: Only what you need, uncluttered
Integrated : Supportive of your CRM
Complete : URL, emails, address, points of contact
Expandable : Data catalysts, URL & social links
#Datafabric
Based on total record count across all silos, choose an appropriate number of random records from silos to perform a data test. What is the state of the data?
Company record completeness (url, address, city, etc)
Contact record completeness (name, email, phone, bio, etc)
Contact record depth/company (number of contacts per company)
Secret 1: Data Test
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A look at CRM, Email systems, lead databases and any silos of information which drives the business. The end goal is to have a solid understanding of:
Business process Vendors used Data flow Known problems Process gaps
Silo interconnectivity Silo latency/data age Silo normalization Silo record count Potential problems
Secret 2: Silo Review (not just CRM)
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Develop a CRM Data Plan which is crucial to the entire project. The CRM Data Plan is used for cleaning, enhancing, de-‐duping, and eventually protecting the CRM from additional duplicates. (Data ShieldTM )
Secret 3: CRM Data Plan
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Websites are the future backbone of company data. Fill in URLs for company records. Some companies have multiple brands and multiple websites. This step is critical to keeping company and contact information fresh. URL fill is critical to resolve ambiguous company names for later deduping.
Secret 4: URL fill
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Secret 5: Email Capture
A large, untapped source of contact information and connection strength lies buried in email archives. Select email contacts based on email counts, names, companies or connection strength. Selected contacts and companies are held for final data reintegration.
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Secret 6: Normalize your Data
Using the CRM Data Plan, all extracted data silos are normalized. Normalized data is ready for deduping.
Deduping will be 600% more effective if Normalization is done first.
(6% dupes vs <1%)
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Secret 7: Address correction
Provides standard address correction. This step can be done before or after the data load back into the CRM. Very large address appends are best done before loading.
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Secret 8: Company ProfilingScan the public web, in real-‐time for contacts at each unique company. Data returned includes names, titles, emails, phone numbers, professional bios and social network links.
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Secret 9: Market Mapping
Add segmentation tags into the account record of your CRM. Industry-‐only categorization is not enough for the demands of marketing automation that requires segmentation for effective campaigning.
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