The impact of data management on marketing efficiency and results


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  • [Welcome…]
  • [Quickly review each statistic]Interesting stats and points to ponder ad we get started with this discussion….
  • You may be familiar with the impact of bad data stats recently shared by SiriusDecisions.[Click x4] These statistics and some of the other things we’ve discussed today underscore the importance of addressing data quality proactively, before its impact is felt. By working to adopt marketing data management best practices, companies will be better positioned to avoid the following risks and impact: • Falling short of revenue goals by not reaching target buyers or leads falling out of the funnel due to being marked unqualified because of bad data;• Damage to brand and sender reputation from poor email deliverability or redundant sends;• Financial impact from increased records storage costs, inefficiencies, or costs associated with duplicate sends, such as in direct mail;• Limited segmentation, low conversions and incorrect lead routing.The good news is that marketing technology is evolving and innovating at breakneck speed. This technology provides marketers with unique opportunities to establish ongoing practices for data management. While companies participating in this study highlight opportunities for improvement, the attainment of healthy data is within grasp for companies willing to invest the time to make a difference.
  • The B2B Marketing Data Benchmark report is based on the NetProspex Data Health Scale, which provides a foundation for the uniform evaluation of a company’s B2B marketing database across four defined Best Practice Areas which we will introduce individually. In addition, the report provides to an overall score of the database marketability. This scale is built on our analysis of over a hundred million records using this process as well as experience gleaned from working with thousands of customers; developing this unique view into the state of B2B data. The scale itself was determined using a combination of primary research to establish market standards, coupled with the results of assessments, known as the NetProspex Data HealthScan, completed to date and statistically determining ranges based on the data.  The NetProspex Data Health Scale is a standardized five-point scale with ratings from “1”, which indicates a “Risky” status, and escalating to “5”, which is “Optimal”. Decimal numbers demonstrate that the overall score falls between two ratings. For example, a ranking of 3.8 communicates that company’s database is past “Questionable” and headed toward “Functional”.  (CLICK--results) Using the NetProspex Data Health Scale, the average health score rating across all industries surveyed showed that most participants' operations were "Unreliable", scoring 2.7 out of a possible 5.  Based on the overall averages, 0% of the participants scored either "Risky" or "Optimal", but many of them did land in those categories for specific practice areas. Now let's take a closer look at who was surveyed.
  • I’d like to introduce the four Best Practice Areas; they are:(CLICK) Record duplication, which is defined as the incidence of repeat records in a B2B marketing database;(CLICK) Record completeness, which is defined as the existence of data populating specified fields targeted for multiple methods of contact as well as basic segmentation and lead routing;(CLICK) Email deliverability, is the measure of whether an email is able to reach its intended recipient; and finally,(CLICK) Phone connectability, which is defined as the ability to reach a contact using the specified phone number in the record. These areas of B2B marketing data best practices provide a foundation for effective demand generation and offer a framework for ongoing efforts to manage marketing data. This report uses these four areas as the platform for key findings.
  • We'll begin with Record Duplication. Redundant records and information cause databases to become bloated, increasing records storage and maintenance costs, or the costs associated with duplicate sends.  (CLICK—the problem) It can impact lead scoring routines when behaviors are tracked separately in different records when they are actually for the same contact. It clouds the ability to accurately calculate ROI for marketing programs and to correctly identify returning customers, resulting in wasted budget and redundant behaviors in marketing and sales teams, which affects brand reputation. When duplicative sends or calls occur, customers and prospects get annoyed.  (CLICK—the results) I’m happy to say that, based on the Health Scale, participant companies ranked an average of 4.3 out of 5. This rating indicates that more than half of participants eliminated duplicates from their databases and most others have significantly reduced the instances of duplicates and their database and, thus, the associated risks that we just reviewed. This may be because many companies employ marketing automation or email service provider (ESP) solutions, most of which have controls that help to identify the occurrence of duplicates, and the success seen in this Best Practice Area gives hope that companies of all sizes can find ways to address duplicates in their own databases by implementing a repeatable process to review and de-duplicate their data. But, marketers that do not have the necessary tools or are not using them face a disadvantage as it relates to redundant records, and record duplication is common and requires focus and resources to eradicate.
  • The second Best Practice area is record completeness. Today, contact records are used for more than simply getting in touch with the prospect or customer.  A complete record includes the following fields… [explain fields] These are the fields that marketers employ for lead routing, content serving, analytics and segmentation purposes, as well as customizing their experience with your company.  Internally, incomplete data presents challenges at all stages of the marketing and sales funnel as programs experience low conversions or the leads can be incorrectly routed to sales, which creates a bad relationship between sales and marketing departments.  A dive into the data reveals differing levels of efficacy by industry. (CLICK—industry statistics) Manufacturing and Telecommunication companies scored 3.5 and 2.8, respectively.  (CLICK—statistics part 2) Conversely, Media & Internet companies tied Energy, Raw Material & Utilities companies with a score of 2.0, which barely keeps the average of those field out of the "Risky" category.  (CLICK—results) In our study, record completeness averages 2.5 across all industries and companies, indicating it presents impairment related to lead scoring, routing and segmentation. Staggeringly, 61% of participants rated as "Unreliable“ or "Risky,“ and said 35% or more of their records were incomplete.  There is a relationship between record duplication, record completeness and record accuracy. The more complete a record is, at least in terms of contact type data, the better chance there is for a software system (or a human) to identify the duplication. Therefore, a strategy to remove duplicates is founded in efforts around accuracy and completeness.
  • The third Best Practice area surveyed is email deliverability.SO why does email deliverability matter? The impact of poor email deliverability are significant and include:The inability to reach customers and prospectsMissed goals in terms of demand generation effortsSender reputation damage from a high incidence of bounces (CLICK—graphic of undeliverability) Overall results of the study indicate that issues in this best practice area are likely introducing unnecessary risk into companies’ email marketing programs. The average company database deliverability was 72 percent, meaning that 28 out of 100 emails sent from this dataset would result in an undelivered email.  How does this happen? As contact records are amassed from a variety of sources and tend to degrade over time, maintaining accurate contact information can be difficult, but it is imperative to marketing outreach. Marketing automation and ESPs can help to hide some of the errors, such as identifying hard bounces and no longer sending to those addresses. While this adds value to ensure marketers are not continuing to negatively impact their send reputation, it does not address adjacent issues, such as the costs for storing incomplete records, missing campaign goals, or damage to sender reputation for initial bounces. But, more importantly, with a high instance of erroneous emails, companies can fall short of marketing revenue goals due to inability to reach target buyers. Thus, the need to weed out the bad data is still there; otherwise, companies will mismanage customers and can become labeled as a spammer.    (CLICK---size) The mid- and enterprise-sized companies demonstrated more unreliability than small companies. We spoke to some of the smaller companies and from what we can tell they are having an easier time managing their databases because they are smaller. (CLICK—industry) And Manufacturing companies scored very well “Functional”, while Media & Internet companies rated an average of “Risky”.  (CLICK—results) But with the average score of 2.8, companies of all sizes and industries illustrate room for improvement. Overall, email deliverability scores ranged from "Risky" 1.75 to "Functional" 4.5, and the average overall health scale rating is 2.8, or below “Questionable”. In fact, 41% of respondents reported email deliverability below 70%.
  • (CLICK—graph of unconnectability) Consider this: The average phone connectability of databases was 42 percent, an indicator that, on average, more than half of the contacts in the databases likely cannot be reached at the phone number included in the record.  (CLICK—phone) This kind of lead leakage in the sales funnel equates to lost revenue and presents a considerable risk to companies. It is a significant problem because if you cannot talk to your buyers, chances are slim you’ll be able to sell them anything. Frustration and lead mismanagement can ensue when a lead arrives with erroneous phone information. One of two things typically happen next: the lead is hastily marked as unqualified or the sales person spends time begrudgingly researching the correct phone information, at a much higher cost to the business than the low cost of data verification or enhancement. In addition to an unneccessary cost, incorrect or missing contact information reflects poorly on marketing in terms of perception of lead quality.   (CLICK—size) Across industries mid-sized companies seem to struggle the most with this issue, scoring 1.1 or “Risky”. This is most likely because of explosive growth in sales, hiring, and data volume. The transition and growing pains may negatively impact data quality as it is considered less of a priority.  (CLICK—results) With scores ranging from 1.0 to 1.5, phone connectability appears to be a major challenge for B2B companies, with an average health scale rating of 1.2, or “Risky”, for participants in the study. In fact, 80% of those surveyed had phone connectability of less than 50%. In terms of customer vs. prospect records, we expected to see stronger scores around customer databases, but saw that they performed similarly to prospect databases.  This, of course, represents additional risk to companies in terms of connecting with customers to ensure their satisfaction, or expand or renew their existing relationship. Overall, the results indicate that participants are performing weakest on the final category--managing phone connectability of their records.
  • To learn more about best practices in record duplication, record completeness, email deliverability, and phone connectability, download the NetProspex 2013 Benchmark Report.  (CLICK—images) We provide greater insights on how to address these issues and enable companies to increase Health Scores to the levels of "Functional" and "Optimal“.
  • To learn more about best practices in record duplication, record completeness, email deliverability, and phone connectability, download the NetProspex 2013 Benchmark Report.  (CLICK—images) We provide greater insights on how to address these issues and enable companies to increase Health Scores to the levels of "Functional" and "Optimal“.
  • DeliverabilityBefore: 74%After: 92%Response RatesBefore: 1.2%After: 3.4%Lead ConversionBefore: .3%After: 1.1%
  • Katie: Do a screen shot of the App here, I will speak to the dataCompleteness before: 39%Completeness after: 94%I will then talk to the impact that had across campaigns, sales teams calling, etc.
  • Story here is about higher conversion rates on forms but better, richer data afterwardForm conversion rate when asking for all data: 4.5%Form conversion rate when asking for minimum & appending afterward: 7.8%OLD**Matt supply fieldsNEW**Matt supply fields
  • Katie will edit this slide. TechProspex2,000 technologies availableHighly-relevant criteria for technology marketersAggregated from big data Story: There is more information available than ever before thanks to big data and companies like ours harnessing it. Take advantage of these data sources to inform your campaigns, targeting criteria, and more. Use case: Confio?
  • But, data quality, accurate records, correct contact information--these elements are crucial to the success of companies across all industries and of all sizes. Here, we've built an overview of how companies can improve their practices. [Read/click through each]
  • Q&A
  • The impact of data management on marketing efficiency and results

    1. 1. Place image hereThe Impact of DataManagement onMarketing Efficiencyand ResultsMichael Bird, CEO - NetProspexMatt Heinz, President - Heinz Marketing Inc.
    2. 2. 2#SDSummit @HeinzMarketing @NetProspexAgenda• The current state of B2B data – Michael• Data management in action – Matt• Q&A
    3. 3. 3#SDSummit @HeinzMarketing @NetProspexThe State of B2B Data:More than48Mpeople changed jobsin 2011188%of IT buyers admit to lyingon registration forms211 US Bureau of Labor Statistics2 Janrain research
    4. 4. 4#SDSummit @HeinzMarketing @NetProspex$100if nothing is doneWhy You Should Care$10 to cleanseand de-dupe itDirty data isn’t just amarketing problem, it’s aBUSINESS PROBLEM!$1to verify arecord as it isentered
    5. 5. 5#SDSummit @HeinzMarketing @NetProspexNetProspex Data Health Scale
    6. 6. 6#SDSummit @HeinzMarketing @NetProspexBest Practice Areas
    7. 7. 7#SDSummit @HeinzMarketing @NetProspexRecord DuplicationAverageHealth Score:4.3Bloated databaseIncreased costs>50%have eliminatedduplicates
    8. 8. 8#SDSummit @HeinzMarketing @NetProspexRecord CompletenessAverageHealth Score:2.561%said 35% or moreof their recordswere incomplete
    9. 9. 9#SDSummit @HeinzMarketing @NetProspexEmail DeliverabilityAverageHealth Score:2.841%reported email deliverability below 70%28%Average % ofUndeliverable Emails
    10. 10. 10#SDSummit @HeinzMarketing @NetProspexPhone ConnectabilityAverageHealth Score:1.258%Average % UnconnectablePhone Numbers80%had < 50% phoneconnectability
    11. 11. 11#SDSummit @HeinzMarketing @NetProspexDownload the Benchmark Report
    12. 12. 12#SDSummit @HeinzMarketing @NetProspexData management in action
    13. 13. 13#SDSummit @HeinzMarketing @NetProspexTIP 1: Know the state ofyour database.
    14. 14. 14#SDSummit @HeinzMarketing @NetProspexTIP 2: Forget the sexy stuff. Clean the data.74%92%DeliverabilityBefore After1.2%3.4%Response RatesBefore After0.3%1.1%Lead ConversionBefore After
    15. 15. 15#SDSummit @HeinzMarketing @NetProspexTIP 3: Using automation? Use the right fuel.39%94%DatabasecompletenessBefore After
    16. 16. 16#SDSummit @HeinzMarketing @NetProspex
    17. 17. 17#SDSummit @HeinzMarketing @NetProspexFill the gaps4.5%7.8%3.0%4.0%5.0%6.0%7.0%8.0%9.0%Form ConversionBefore AfterJohnSmithJsmith@Acme.comACME Inc.
    18. 18. 18#SDSummit @HeinzMarketing @NetProspexTIP 4: Take advantage of big data insightsTech install data delivered:- Higher response rates- Lower unsubscribe rate- Higher lead conversionsDatabaseAdministratorUnknownDatabaseAdministratorrunning Oracle or SQL“…The install data from NetProspex gave me the confidencethat we’ll be targeting the precise audience we want.”Alisa Goldschmidt, Confio Software
    19. 19. 19#SDSummit @HeinzMarketing @NetProspexFundamentals for ImprovingData QualityMake regular (at least quarterly)cleansing of the database abusiness mandate.Make your inbound sources workbetter with registration appendservices, input masks, drop downselections and progressive profiling.Employ best practices whenpurchasing list data.Conduct a DataHealthScan tofigure out where you stand.
    20. 20. 20#SDSummit @HeinzMarketing @NetProspexYour turn: questions?mbird@netprospex.comMichael BirdCEO / NetProspexmatt@heinzmarketing.comMatt HeinzPresident / Heinz Marketing