Tag: Data Quality

NetProspex: 18 Months Since Acquisition and Thriving

Workbench-Deliverable-website-450x280
D&B NetProspex Workbench Data HealthScan report provides a free PDF detailing pre and post enrichment field population rates, data error rates, and segmentation reports.

Oftentimes when a small company is acquired, it is treated as a cash cow (if it is producing cash) or plugged into a larger business to address a capabilities gap or generate cross-selling opportunities.  Less frequently is the new asset treated as a vital, strategic asset to help enter new markets.

Audience Solutions

In the case of Dun & Bradstreet’s acquisition of NetProspex, the acquired division has been a keystone for Dun & Bradstreet’s entry into Audience Solutions (Visitor ID, Audience Targeting).  Dun & Bradstreet is beginning to gain traction in the programmatic advertising space.  On their most recent earnings call, CEO Bob Carrigan noted that their customers have long relied on Dun & Bradstreet for company data, but that this data was difficult to map to online activities because people surf the net, not companies.  When the firm acquired NetProspex early last year, they immediately set out to combine the NetProspex contact data with Dun & Bradstreet firmographics and D-U-N-S Numbers.

“Our contact data, coupled with our company data, on boarded for the digital world and matched to online cookies, helps our customers get their advertising in front of the right target, and the right decision maker at that target, at the right time,” said Carrigan.  “And, by organizing around the D-U-N-S Number, our customers can finally connect their offline customer management data with their online advertising campaigns, creating that vital bridge between ad tech and marketing tech.”

Dun & Bradstreet data is then mapped to three hundred online segments.  These segments utilize anonymous data including size variables, industry, job function, propensity to purchase specific products, and likelihood of qualifying for loans or company credit cards.  Segments are then delivered to partners including Oracle, Adobe, Google, Xaxis and Nielsen.  Furthermore, the firm’s global direct sales team offers bespoke segments for custom targeting.

“[The] whole programmatic wave, it’s all moving to B2B right now. And we’re starting to see some really nice uptake because we’re available for all the major buying platforms,” said Carrigan.  “We’re also selling direct licenses to marketers as well and obviously we’ve got a portfolio already of sales and marketing solutions.  This is a really nice complement to that and we’re trying to catch this wave and really deliver scale in a market that’s highly fragmented. So we’re pretty excited about this. It’s a great example of leveraging our core data in a new use case and it’s a great place for us to be.”

Adding Value to Hoover’s

Dun & Bradstreet also moved to quickly integrate NetProspex contacts into its Hoover’s sales intelligence service and used the NetProspex CleneStep contact verification process to validate Hoover’s contacts.  The result was a deeper set of accurate contacts within Hoover’s and other Dun & Bradstreet contact-based offerings.  The swap also saved Dun & Bradstreet several million dollars in contact acquisition costs.

NetProspex is also one of Hoover’s new Concierge Services for SMBs.  Concierge services are turnkey marketing services for SMBs that have limited marketing resources.

Investing in NetProspex

A further sign of the strategic importance of NetProspex is the continuing investment in the NetProspex Workbench service.  Workbench is a cloud-based data hygiene hub which verifies contacts (phone, email, and address), enriches the records with firmographics and technographics, provides segment and data hygiene analytics, and delivers net-new contacts.  Their data health report is a slick PDF analysis of contact file health and segmentation.  It is given away free as it also promotes Workbench enrichment (pre and post enrichment rates) and prospecting services.

The first thing that D&B did after acquiring NetProspex was swap out the weak firmographics attached to NetProspex contacts and replace them with D&B firmographics from their WorldBase file.  This provides NetProspex with both more accurate firmographics and a much deeper set of company linkages.

Why linkage is important: Each new lead should be scored to determine whether to nurture the lead or send it immediately to a sales rep.  Linkage data ensures that contacts associated with subsidiaries or branches of current customers and prospects are immediately forwarded to the appropriate sales rep.  Furthermore, qualification is based upon the parent company, not simply the size information of the subsidiary or branch.  Finally, channel conflict is reduced if leads are properly routed to the appropriate sales rep.  Reliable firmographic and linkage enrichment provides a neutral third-party source for lead routing.

In January, NetProspex released a new dashboard set to its Workbench cloud-based data hygiene products.  According to Dun & Bradstreet, “The dashboards keep track of consumption levels and alert you when you are in need of Targeted Data or a Data HealthScan. Now you can also gain insight into your Eloqua connectors in terms of performance and data enrichment.”

Data Management subscribers now see a Data HealthScore meter which indicates the overall quality of their most recent data HealthScan.  They are also shown data management scores over time.

NetProspex Data Health Optimizer Report (Workbench)
NetProspex Data Health Optimizer Report (Workbench)

Target Data subscribers can view the total number of contacts acquired over time and a Current Consumption meter which shows “the exact percentage of contact data you have consumed.”  NetProspex also added calendars to the service indicating the last time data was managed by the platform and the recommended next action date.

Finally, NetProspex increased the number of US contacts to 42 million.  Each of these contacts includes an email and a significant percentage contain direct dial numbers.

Data Analytics

While the Workbench service has long offered analytics, NetProspex recently added two analytical models to their Targeted Data subscriptions fulfilled by its Workbench platform.  The two scores assist with segmentation, lead scoring, and messaging.  Spend Capacity is based upon “non-traditional predictive segments such as UCC filings, inquiries and SIC revenue %.”  The predictive score ranks the spend capacity of a firm between one and one hundred.

The second modeled score is Growth Trajectory which “anticipates the future growth or decay of a business based on a mix of criteria including revenue, borrow levels, credit inquiries, order frequency and spend levels.”

Targeted Subscriptions help marketers scrub their marketing database of poor or outdated leads.  Records are standardized, verified (phone, email, and address), and enriched with Dun & Bradstreet company and contact data (42 million US B2B contacts with emails and direct dials).  The subscription then maintains the marketing dataset and replaces bad records with good ones.  The service includes Workbench Analytics concerning segmentation, technographics, and data quality.

“Data analytics (based on facts not probabilities) have not been readily available to the average marketer. That’s no longer the case. D&B is leveraging our deep expertise in understanding and analyzing company data and providing analytical insights as a value-added dimension to our Targeted Data Subscribers — no data scientist or fancy software needed,” says the firm.

Optimizer

According to Carrigan, Dun & Bradstreet generated more than ten million dollars in cross-sales revenue in its first year.  This would include both cross-selling contact hygiene and enrichment services from NetProspex into the Dun and Bradstreet customer base and selling Dun & Bradstreet services to NetProspex clients.  A key cross-sale is NetProspex contact enrichment and D&B Optimizer company enrichment sales.  Optimizer lacked contact enrichments so NetProspex closes that gap.

What’s more, Dun & Bradstreet recognizes that the Optimizer platform needs to be modernized and announced plans to build company Optimizer services on the Workbench platform.  Once completed, Workbench will provide a broader utility to marketers that need both lead (contact based) and account (company based) enrichment of their marketing automation platforms and CRMs.

ABM: The Art of the Start (Avention)

This morning, sales and marketing intelligence vendor Avention unveiled a survey and set of recommendations on implementing Account Based Marketing strategies.  ABM is quickly moving from a buzzword to an actionable strategy for strategically targeting your best customers and prospects.  If you are considering an ABM strategy or researching how to move forward with ABM, Avention’s “Account-Based Marketing: The Art of the Start – Leveraging a Strong Data Foundation to Fuel ABM Success” guide is now available.

The Avention Survey of over 100 top level B2B executives (e.g. CEO, CMO, VP of Sales) found that ABM strategies require “careful data-driven planning, execution and monitoring.”  Furthermore, the lack of data access and quality are “fundamental impediments” that need to be resolved for ABM strategies to succeed.

ABM is based upon strategic targeting of your best accounts and similar companies.  If your underlying data is poor you will have problems with best customer cloning, account messaging, and drilling deeper into organizations for cross-sell and upsell.  Furthermore, “once a program is started, it is essential that account and market news and events be monitored to ensure programs remain relevant.”

Todd Berkowitz, research vice president for Gartner1 wrote in a January report, “By getting a better view of customer data, creating predictive models, employing account-based marketing, and creating internal and external-facing content specifically for existing customers, even marketing leaders from smaller providers can increase the likelihood of success.”

90% of the surveyed B2B execs believe that ABM is relevant to their organization and 86% are confident that ABM will drive growth; however, 75% are having trouble finding the appropriate contacts for selling deeper into target organizations, and more than fifty percent of B2B marketers lack an ability to monitor and adjust programs directed towards ABM accounts due to a lack of real-time intelligence.

AV ABM Survey
ABM Survey of B2B Executives republished with permission from Avention.

Avention noted that ABM is a long-term strategy that requires continuously updated account and contact intelligence if campaigns are to remain relevant.  For example, messages and offers may need to be adjusted due to key events such as executive changes.

Avention CEO Steve Pogorzelski summarized the ABM implementation problems found in the survey:

Almost two-thirds of the marketers responding to our survey report not having access to a single source of truth for customer data.  This obviously impedes starting an ABM program and running it to successful conclusion, as such programs demand access to accurate and continually updated market and account data.  ABM offers enterprises the opportunity to quickly fuel their customer acquisition, growth and retention strategies.

Pogorzelski noted that Avention provides three capabilities which support sales, marketing, and sales operations ABM responsibilities:

  • Marketing: “Consolidation and visualization of in-house customer data for sophisticated segmentation.” (For more on these capabilities, see my February blog on the launch of their DataVision platform).
  • Sales: Strategic intelligence concerning companies and contacts along with predictive indicators.
  • Sales Operations: CRM and Marketing Automation ecosystem connectivity.

Finally, I would note that traditional approaches to marketing data quality which involve annual data cleanses are insufficient to meet ABM and predictive marketing needs.  Marketing data, particularly contacts, ages quickly.  The lack of a continuous data quality strategy will result in a drop-off in sales and marketing productivity as contact and company data decays.

1 Gartner, Tech-Go-to-Market: Four Ways Marketers can Generate Demand with Existing Accounts, January 29, 2016

Full Disclosure: I broadly advise companies across the sales intelligence space including Avention.  While I periodically write commissioned blogs for Avention, none of my commentary on my own blog or social media accounts is commissioned.

Data.com: Price Reduction & Product Line Simplification

The Data.com Corporate Hierarchy Viewer displays the Dun & Bradstreet family tree. Users can add any location as an account. The tree also shows sizing variables and SFDC account owners.
The Data.com Corporate Hierarchy Viewer displays the Dun & Bradstreet family tree. Users can add any location as an account. The tree also shows sizing variables and SFDC account owners.

Data.com has simplified its pricing from two tiers to a single tier for both its sales intelligence Prospector service and its data hygiene Clean offering.   All Prospector users now receive the full Dun & Bradstreet WorldBase record for $150 per seat per month.  The full Dun & Bradstreet file was previously priced at $165 per seat per month as part of the Premium offering.  Corporate users will see the price rise from $125 to $150 but will receive the following additional content and capabilities due to the product unification:

  • Corporate family linkages with domestic and global ultimate parents
  • Corporate family hierarchy viewer
  • Up to six total SIC/NAICS industry classification codes
  • Account tradestyle (Doing Business As)
  • Account delinquency risk (High/Medium/Low)
  • Account latitude and longitude
  • Hoover’s First Research call prep content for imported and matched company records
  • Additional Hoover’s data/content, including Net Income, Industry Opportunities and Competitive Landscape

Users are still limited to 300 uploaded or downloaded records per user per month.  Additional records are priced at $0.65 per record, unchanged from the previous premium offering.  Data.com counts both company and contact records towards the monthly limit.  Additional download record credits are not subject to monthly usage limits and may be allocated to Prospector accounts at the Salesforce Administrator’s discretion.

The Clean service price is now $25 per user per month for all users in the instance.  All Clean users now receive the full WorldBase file.  By standardizing clean to a single edition, Data.com has reduced the price of Clean Premium from $35 to $25.

Simplifying the product bundles makes sense.  For premium users, there is a small price cut while there is a price rise for corporate users of Prospector but not Clean.  As a premium to Salesforce, having two Data.com editions probably complicated sales discussions unnecessarily.

Lowering the price of Clean also makes sense as higher data quality raises the overall value of the CRM for sales, marketing, and support.  Marketing enjoys better segmentation and targeting while sales benefits from improved company intelligence for qualification and fewer misrouted leads.  Sales and support also benefit from the better population of contact information (e.g. direct dials, phones) and flags when an individual is no longer affiliated with the account.

While the price reduction makes Prospector more competitive with other Sales Intelligence solutions, Prospector remains at the upper end of the market.  For example, InsideView for CRM is priced at $995 per annum, 44% below the price of Data.com Prospector.

Still Not Convinced that Data Quality Is an Issue?

 

Integrate evaluated over 750,000 records from B2B companies and found consistent data problems whether the firm was and SMB, Enterprise, or Media Company. In each case, roughly 4 in 10 records contained inaccurate or bad information.
Integrate evaluated over 750,000 records from B2B companies and found consistent data problems whether the firm was an SMB, Enterprise, or Media Company. In each case, roughly four in ten records contained inaccurate or bad information.

While the primary theme of my blog is sales intelligence, you cannot have sales intelligence if your databases are rife with duplicate records, invalid emails, missing or incorrect firmographics, and non-standardized values.  These errors wreak havoc on marketing and sales.  I came across a 2016 Integrate report that had a series of quotes on the subject which addressed the impact of bad data quality across multiple marketing activities:

The issue of data quality continues to be one of the biggest roadblocks to effectively analyzing the prospect and customer journey. It also dramatically increases the costs of analytics projects and negatively impacts performance.
– Sameer Khan, Sr. Product Marketing Manager, IBM Customer Analytics

Dirty data is the silent killer of marketing campaigns. It makes you look bad, depresses the impact of great content and offers, and can put your brand, reputation and domain at risk (or worse).
– Matt Heinz, President, Heinz Marketing

Data is the oil of any marketing engine, and in order to create perpetual demand generation, data accuracy needs to be a top priority. Marketers must be ruthless and deliberate about data quality and standardization at point of entry.
– Jonathan Burg, Sr. Director, Marketing+Customer Acquisition, Apperian

And if you still aren’t convinced that data quality can choke your initiatives, their research found that 40% of B2B records have some form of data quality issue with duplicate data representing 15% of your marketing database.  Invalid Values and Ranges (10%) and Missing Fields (8%) were also common problems.

So if forty percent of your marketing data is faulty, then a significant percentage of your Marketing Qualified Leads passed to sales will contain errors including contacts not at companies (not evaluated by Integrate but contacts decay at a 25% rate per annum), and bad firmographics resulting in wasted time, incorrect routing,  inaccurate lead qualification, and poor messaging.  Furthermore, initiatives such as account based marketing (ABM), account based sales development (ABSD), and predictive analytics will stall if they are fueled by bad data.

Data Quality Isn’t Glamorous — Now Get over It

The Data Health Scan Report is one of the Optimized Customer Data Services.
A Data Quality report is an excellent way to start a data quality program.  It helps with sizing the problem and providing an initial remediation cost.

Unfortunately, data quality is a boring topic. No new CMO has ever joined a company and said, “First, let’s perform a merge/purge on our account and contact records, standardize the fields, and enrich the records.” (OK, I’m being hyperbolic, there may have been a few). No, they want a shiny new marketing automation platform, new branding, and an advertising campaign that gets the company noticed.

Sadly, there is little glory in improving your marketing database — unless, of course, you want to improve your lead nurturing, scoring, segmentation, routing, and sales ready lead quality.

Quality is generally seen as a cost center but it can just as easily be viewed as a cost saver. Bad quality erodes your marketing effectiveness, hurts your brand, kicks the knees out from under your nascent big data experiments, and demoralizes sales reps. A bad company or contact record is like a virus propagated from system to system raising the cost over time.

Furthermore, how can you think about predictive analytics when your databases are rife with bad, incomplete, and out of date records?

Bad data isn’t simply a mistyped address. It’s also:

  • Missing lead firmographics making it difficult to nurture, score, route, and qualify leads.
  • Invalid emails that hurt your deliverability scores and decrease the likelihood your messages will be delivered to inboxes instead of spam folders.
  • Junk fields on web forms because the individual didn’t want to fill out a dozen fields to read your whitepaper.
  • Large gaps in your segmentation analysis labeled UNKNOWN.
  • Hosting costs for storing out of date and duplicate data.
  • Leads with missing linkage that were held for nurture because the marketing automation system didn’t know the location was a subsidiary of a Fortune 500 company.
  • Poor marketing messaging and targeting that tell the recipient that you know nothing about their business, job function, industry, or company size.

Finally, bad lead quality incentivizes sales reps to ignore leads because marketing never seems to send the “Glengarry” leads. Instead, they become demoralized as they call invalid phone numbers or find that the contact “doesn’t work here anymore”.

Henry Schuck, CEO of DiscoverOrg, describes the situation well:

Sifting through crappy leads as a sales person is incredibly demoralizing. Their commission – which often translates into their ability to save for their family’s future, have disposable income or cover their mortgage and car payments – depends on them being able to close business. Their ability to close business, in turn, depends solely on their ability to find, set appointments with, and CLOSE new opportunities. If the leads provided by your company will not help them do that – how does that feel? They just moved companies to come work for you and their future is uncertain, at best.

So look at data quality holistically. Address it at the front end in your call centers and web forms and then enrich and maintain your database over time. As contact records decay at a 25% rate per annum you need to view data quality as an ongoing process, not simply an annual refresh (which is more than many companies even do).

So by flipping your perspective, it is easy to find myriad tangible benefits which justify the cost of data quality programs. It may not lead to glory, but by recognizing the distributed costs of bad data and then remediating them, you can generate significant ROI.

Photo Credit: Data Hygiene report from Dun & Bradstreet NetProspex Workbench

Hoover’s Concierge Services for SMBs

The Data Health Scan Report is one of the Optimized Customer Data Services.
The Data Health Scan Report is one of the Optimized Customer Data Services.

Hoover’s began rolling out a set of concierge services for small businesses after being merged into the Emerging Business unit last summer.  Dun & Bradstreet CEO Bob Carrigan has positioned the new services as important to turning around the Hoover’s product line which has been struggling of late.  In December, Carrigan noted that the new services have had “good success.”

The Concierge services target SMBs with revenue up to $250 million.  Concierge services target the standard Hoover’s B2B verticals including technology companies, business services, financial services, and manufacturing.

Dun & Bradstreet Product Leader (S&MS Solutions) Michael Umbach noted that the company has long received requests for assistance with customer marketing.  Dun & Bradstreet is meeting this need by combining their expertise with their data and solutions to help customers implement targeted list building, marketing file enrichment, and marketing campaigns.  Furthermore, Dun & Bradstreet Credibility Corp, which was acquired last May, has had success offering concierge services to SMBs for credit products.

The services enable customers to perform targeted marketing without requiring them to add marketing headcount.  According to their website, “Our experts can serve as an extension of your marketing team, helping you find—and reach—your best customers.”  The underlying services utilize the Hoover’s, Optimizer, and NetProspex WorkBench (aka Optimizer for Contacts) platforms for fulfilling customer needs.  Dun & Bradstreet has also partnered with an undisclosed email platform to support email services.

Hoover’s is providing three related services for SMBs:

  • Targeted List Building – Identifies prospects similar to a client’s best customers.
  • Effective Email Marketing – Delivers email services including messaging, design, email coding, blasting, and testing.  Dun & Bradstreet also supports email verification, analytics, and unsubscribe / bounce management.  Landing site hosting is provided via an undisclosed partner.
  • Optimized Customer Data – Supports data cleansing, standardization, and data enrichment for customer company and contact files.

As a promotional tool, Hoover’s is offering a free data quality check which assesses email deliverability, phone connectivity, and duplicate records.  This service would be provided by their NetProspex Workbench platform.

Many of the Concierge clients are signing up for a full year of service allowing them to run multiple campaigns, target different audiences, and maintain and enrich their marketing data files.

The acquisition of NetProspex has also directly benefited Hoover’s users.  Following the acquisition, the NetProspex contact file was merged into the Hoover’s contact set.  Furthermore, the professional contacts file was processed through NetProspex CleneProspex validation process.  Umbach noted that the improved contact data quality has raised customer satisfaction around contacts.

Avention Launches DataVision for Marketers

DV1

Late last month, Avention announced availability of OneSource DataVision, a hosted marketing platform which integrates internal and external customer intelligence.  By matching Avention company and contact data against customer and prospect files, Avention improves the accuracy and firmographic fill rates of marketing databases.  The result is improved customer segmentation and targeting based upon enriched data from Avention’s Global Live database of companies and contacts.

DataVision also provides analytics and visualization tools for marketers.  “As a result, you will be able to identify and leverage key customer and prospect segments to make more informed decisions, identify cross-sell opportunities, key industries, verticals and much more,” states Avention.

“In a world where gaining new customers has become more complex and competitive, and customers engage with vendors later in their buying processes, marketing and sales teams need to align their data more than ever. OneSource DataVision is a powerful – yet easy-to-use – tool that helps marketers understand their current customer bases in detail and identify the most relevant target companies and segments,” stated Lauren Bakewell, SVP of product for Avention. “Initial customers have seen positive business impacts and results from their use of OneSource DataVision.”

DataVision provides a centralized marketing view of customer data which may be housed across multiple platforms including CRMs, Marketing Automation Platforms, and order entry systems.

“Companies need accurate, deep data to gain the marketing intelligence needed for better targeting and advancing customer relationships.  The ripple effects of greater marketing intelligence within the enterprise are improved sales cycles, cost of lead and sale and revenue generation,”  blogged Jennifer Nash.  “OneSource DataVision helps marketers increase the value of existing customer and prospect data by centralizing, analyzing and visualizing multiple data sources.”

DataVision includes a gap analysis tool which assesses the total addressable market in order to identify underserved markets and growth potential.  After enriching and segmenting the data, DataVision users can prospect for similar companies.

DV2
DataVision Look-Alikes segmented by state.

 

As DataVision provides ongoing cloud based data cleansing and standardization, It is likely to be competing against similar offerings from ReachForce, Zoominfo, and D&B NetProspex.  The service is also likely to butt up against predictive analytics companies such as Lattice Engines and Infer.  While Avention offers a set of predictive tools (e.g. Business Signals and Ideal Profiles), they do not appear to be fully integrated into the initial release.

Analyst David Raab noted that DataVision’s hosted data model is likely to result in fresher data “since any query to DataVision will return the latest information available to Avention.”  He also complimented DataVision’s visualization tools and the platform’s ability “to compare those distributions with the entire Avention universe of known firms.”

A significant trend over the past two years has been the blurring of the lines between sales and marketing with sales intelligence vendors addressing marketing requirements (e.g. DataVision, Zoominfo,  InsideView for Marketing) and marketing functions migrating down the pipeline to sales reps (e.g. SalesLoft Cadence, Salesforce IQ).  Historically, OneSource shied away from building marketing tools in order to focus on the sales and research functions.  While they long offered match & enrichment services, this offering was managed by their Professional Services team as either a custom project or CRM enrichment.  DataVision is their first product designed specifically for the marketing team.  Of course, improved data quality at the top of the funnel provides benefits to sales reps in the form of improved lead quality, enriched leads, and properly routed opportunities.

Data Science and Competitive Advantage

GlassDoor Tech Salaries

Social media job site Glassdoor recently published its second annual ranking of the top jobs in America and, of the top twenty-five jobs, ten were in technology.  The top ranked position was data scientist which jumped from ninth last year.  Other high ranked positions were Solutions Architect (#3), Mobile Developer (#5), and Product Manager (#8).  Glassdoor bases their rankings on three variables: the number of job openings, salary, and career opportunities rating.

The Median Base Salary for a data scientist is $116,840.  Other tech base salaries can be seen in the above graphic.

When Network World interviewed data scientists about their position, they noted the pleasure of discovery as a key benefit.  A common complaint amongst data scientists was the headache involved with data preparation.  “At times, munging [parsing] through data can get tedious,” said data scientist Jeff Baumes at Kitware. “The worst times are when I realize the quality, quantity, or other aspect of the data simply prevents me from gaining the level of insight that I hoped to gain from the data.”

The McKinsey Global Institute found there is a growing shortage of analytics talent in the United States.  By 2018, they projected a shortfall of 140,000 to 180,000 professionals with analytical expertise.  They also projected a deficit of 1.5 million analytics trained managers and analysts.

Data scientist talent acquisition and retention are a significant problem for organizations, particularly amongst firms looking to initially establish data science capabilities.  In an article in the MIT Sloan Management Review, Ransbotham, Kiron and Kirk Prentice found that 55% of analytically challenged firms had a problem recruiting and retaining analytical talent while firms described as innovators had much less difficulty.  Only 29% of innovators reported difficulty recruiting with 24% reporting difficulty retaining.  Innovators also are much more confident that they have the appropriate skill levels in house.  While 74% of Innovators believe they have hired the appropriate analytics talent, only 17% of the analytically challenged felt the same.

One advantage of partnering with sales predictive analytics companies such as Lattice Engines or Leadspace is the ability to bypass hiring of in-house data scientists and instead work with their resources and tools.  While it is still important to understand the results and train staff in data interpretation, much of the complexity is removed.

Furthermore, the strategic advantage accruing to analytics capabilities is declining as more firms develop such capabilities.  In 2012, 67% of surveyed respondents believed analytics capabilities conveyed a strategic advantage.  By 2014, the percentage had dropped to 61%.  The authors posited two reasons for the decline: an increase in the number of firms investing in analytics and a difficulty in converting analytical insights into business action.  Half the respondents noted difficulty in translating insight to action.

“Technology is no longer the main barrier to creating business value from data: The bigger barrier is a shortage of appropriate skills,” said Ransbotham et al.  “Companies with appropriate analytical skills are far more likely to say that analytics is creating a competitive advantage in their organization than are other organizations.”

Owler: Jim Fowler on Crowdsourcing Content

Owler Profile of Lyft

Jim Fowler, who founded three crowdsourcing startups (Jigsaw which was acquired by Salesforce.com and renamed Data.com,  InfoArmy, and ), was asked how crowdsourcing has changed over the past decade.  His observation was broader than crowdsourcing and applied to any tech company looking to gain mindshare:

I think they change in the same way that we all have. We all are just overloaded with information.  Getting people’s time and getting them to pay attention is much more difficult now than it was back in the beginning of Jigsaw for sure. Getting journalists and analysts to talk and write about you is different because there’s so much going on. In fact a lot of the big publications don’t even exist or don’t write about it anymore.

It’s become much more flat, if you will. More players in it, so that’s interesting, but I just think the biggest thing is just people … There’s so much stuff flying around out there now that really making sure you have a crisp clear message so that they understand the value is even more important than it ever was and that’s just been the big change. People are more sophisticated, they’re more … They know how to use data and I see that trend continuing.

Fowler also noted that Owler combines crowdsourcing and semantic mining with editors.  While machines can do much of the work around event aggregation and structured alerts for exec changes, M&A, and funding rounds, editors ensure that information is properly tagged and mapped.  While this editorial review of news introduces a short delay in information delivery, it reduces the number of false positives and passing mentions of companies.  Furthermore, it allows them to de-dupe the stories and accurately capture M&A and funding content.

Basically, it solves your signal to noise problem through the addition of a short editorial review step.

If you just used technology to try to do this, you would get a lot of noise in there because really it’s a lot harder than it looks to figure out that the article is actually about Apple. Apple gets mentioned in millions of articles. To know that it’s actually about Apple is … To just do it with technology is really hard. What technology can do is say, “We think this is an article about Apple and we think it’s an Apple acquisition and we think this is the company that they did and we think this is it,” but what you need to do is create a task that gets prioritized very highly that a human looks at really quick. Checks out all the data and goes, “Ah, that’s right. We’re good,” and then sends it on to the people.

Otherwise you get a lot of noise, what I’m getting at is that technology can get you way down the road, but you need humans to get you all the way down the road if you want high quality data.

It is this multi-process approach that is likely to be the future of data collection and aggregation.  Traditional methods of data collection via phone interviews or analyzing filings information are quite expensive while semantic mining can get tripped up on context (is this about company X? Is this a relevant story? Is this a discussion of current events? Is this an actual event, proposed event, or mere rumor?).  Likewise, crowdsourcing requires a very large audience to obtain the wisdom of the crowd and works best on easily defined fields such as address, phone, and email (i.e. Jigsaw contacts).  Crowdsourcing also works well at gauging sentiment.  For example, Owler captures sentiment around whether the CEO is doing a good job and the projected fate of private companies.  But crowdsourcing does a poor job around complex information such as industry code tagging or corporate linkage.  It is through complementary methods that vendors will drive qualify forward while keeping data costs in check.

Radius: Bad Data Is a “Rotten Ingredient”

640px-rotten_oranges

Stephanie Kong, Product Marketing Manager at Radius, recently compared dirty data to rotten food.  Working with either consumes more expertise and results in sub-par results:

Handing dirty data over to data scientists is tantamount to passing rotten ingredients to a chef and expecting that he/she transform the inputs into a gastronomical masterpiece. In both instances, the quality of the inputs impacts not only the quality of the outcome, it also impacts the experience and efficiency of the professional– how much time can be spent experimenting and applying the artistry for which the professional was hired versus overcoming hurdles to get to a sufficient baseline.

Bottom line: the quality and state of your internal data can impact– and even worse, impede– the ability of even the most talented data scientist to generate breakthrough ideas. Many turnkey data solutions can help you maintain data, even enhancing accuracy and comprehensiveness, in addition to extracting insights. It’s not simply a means of “killing two birds with one stone”; accurate and complete data is a critical first step. In other words– and without being too macabre– good data is the essential and necessary “first kill.”

Marketers are becoming more strategic in their approach to data as they realize the limitations and costs of poor data.  Predictive Analytics systems are only as good as your underlying data.  Bad data is simply noise (or as Kong would call it, “rotten ingredients”) that obscures the underlying signal.  Without accurate data, how can you expect your predictive systems to give you anything more than random nonsense?

Likewise, the shift to Account Based Marketing requires strong firmographics for identifying the companies you wish to target.  Furthermore, strong linkage is necessary for targeting subsidiaries and branches.  Whether you are extending an MSA or looking to establish a beachhead, you need a holistic view of the organization across industries, regions, and job functions.  You also need an accurate set of contacts spanning all functions, levels, and locations.

When evaluating B2B content vendors offering predictive or DaaS solutions, ask about their

  • Data Processes: Data sourcing, update cycles, verification and validation, feedback processes
  • Hygiene Services: Do they offer email, phone, and address verification, field standardization, deduplication
  • Matching Capabilities: Is it a direct match or probabilistic match based upon multiple fields? Are fields standardized prior to matching? Is the focus on company or contact matching?
  • Connectors / Integrations: CRM, MAP, DaaS cloud, API, etc.
  • Ongoing Data Refreshes: Frequency, Cost, Level of Automation
  • Contact Coverage: Emails, direct dials, functions, levels, bios,
  • Company Data: Scope, depth, firmographic fill rates, identifiers, linkage, etc.
  • Other Data: Intent data, technology platforms, business signals, etc.

Data quality is a strategic asset so your content and technology partners need to be thoroughly vetted.  It is important to understand the strengths and weaknesses of each offering during both the vendor selection and implementation stages.  Otherwise, you may only partially address your “rotten ingredients” problem.

Photo: Wikimedia Commons