Diese Präsentation wurde erfolgreich gemeldet.
Die SlideShare-Präsentation wird heruntergeladen. ×

eMarketer Webinar: Predictive Marketing—Using Data Decisively at Every Stage of the Funnel

Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige
Anzeige

Hier ansehen

1 von 54 Anzeige

eMarketer Webinar: Predictive Marketing—Using Data Decisively at Every Stage of the Funnel

Herunterladen, um offline zu lesen

A typical brand now has a staggering amount of data in its arsenal, and the marketing department’s goal is to use that data to deliver more effective results than ever before. Enter predictive marketing, which uses machine learning to deliver more accurate insights about how best to encourage sales from existing and new customers. Topics in this webinar include: What marketers are doing with predictive models; How many companies have moved toward predictive marketing, and how far along they are; What the return on investment (ROI) of predictive marketing can look like; Which challenges are proving difficult for adopters of predictive marketing.

A typical brand now has a staggering amount of data in its arsenal, and the marketing department’s goal is to use that data to deliver more effective results than ever before. Enter predictive marketing, which uses machine learning to deliver more accurate insights about how best to encourage sales from existing and new customers. Topics in this webinar include: What marketers are doing with predictive models; How many companies have moved toward predictive marketing, and how far along they are; What the return on investment (ROI) of predictive marketing can look like; Which challenges are proving difficult for adopters of predictive marketing.

Anzeige
Anzeige

Weitere Verwandte Inhalte

Diashows für Sie (20)

Andere mochten auch (13)

Anzeige

Ähnlich wie eMarketer Webinar: Predictive Marketing—Using Data Decisively at Every Stage of the Funnel (20)

Weitere von eMarketer (15)

Anzeige

Aktuellste (20)

eMarketer Webinar: Predictive Marketing—Using Data Decisively at Every Stage of the Funnel

  1. 1. © 2016 eMarketer Inc. Made possible by Predictive Marketing—Using Data Decisively at Every Stage of the Funnel Jillian Ryan Analyst June 23, 2016
  2. 2. © 2016 eMarketer Inc. Today’s Agenda  Predictive analytics and marketing defined  The importance of data in building predictive models  Exploring predictive applications across the customer funnel  Measuring predictive marketing’s value  The current state of adoption and what’s on the horizon
  3. 3. © 2016 eMarketer Inc. Defining Predictive
  4. 4. © 2016 eMarketer Inc. Many B2B marketers in the US don’t understand the benefits of predictive analytics
  5. 5. © 2016 eMarketer Inc. Predictive analytics delivers more accurate insights  Predictive analytics uses predictive models to estimate which marketing actions are most likely to pay off in the future  With more accurate insights, marketers can determine how to best encourage sales from existing and new customers
  6. 6. © 2016 eMarketer Inc. It’s all about the data—and it’s getting more sophisticated  The way B2B marketers are using data is evolving  Predictive is rooted in forward-looking analysis  Rather than relying on guesswork, predictive is based on a trusted, analytical fact
  7. 7. © 2016 eMarketer Inc. Data: The Engine Powering Predictive Technology
  8. 8. © 2016 eMarketer Inc. Marketers are using data, but sophisticated practitioners are winning 90%+maintained databases on customers/prospects, segmented data for targeting, and measured campaign results across channels Source: Global Alliance of Data-Driven Marketing Associations and Winterberry Group, Sept 2015 50%+considered themselves sophisticated practitioners, while the remaining portion were just performing these data-driven approaches to some extent
  9. 9. © 2016 eMarketer Inc. Historical data reveals patterns in behavior  Data tells a story based on the past experiences it has recorded  Predictive analyzes data touchpoints to determine patterns  It learns from data to render predictions
  10. 10. © 2016 eMarketer Inc. The most common types of data used for predictive marketing included:  Website data (47%)  Demographics (44%)  Digital transactions (41%)  Social (39%)
  11. 11. © 2016 eMarketer Inc. Data touchpoints must be managed properly Top DQM services included:  Big data  Master data management  Data cleansing and validation
  12. 12. © 2016 eMarketer Inc. Bigger companies are more likely to leverage historical campaign analytics for predictive modeling
  13. 13. © 2016 eMarketer Inc. Marketers face several challenges leveraging historical data for predictive:  Too expensive  Lack of expertise  Vendor tech isn’t mature enough  Hard to prove value
  14. 14. © 2016 eMarketer Inc. Machine learning delivers fact-based predictive insight  The machine ingests data from past successes and failures, then runs a model to deliver predictive scores for various desired outcomes  68% of respondents used it for predictive analytics
  15. 15. © 2016 eMarketer Inc. Ensuring accuracy in the predictive model requires two types of data: Training Data  Used to construct the model  The majority of data points available Testing Data  Used to verify the predictive model’s precision  A small subset kept separate from the training data
  16. 16. © 2016 eMarketer Inc. As the machine learns, the model gets smarter  The predictive engine continues to learn from data touchpoints  With more experience it renders more accurate predictions
  17. 17. © 2016 eMarketer Inc. Predictive Marketing: Putting Insights into Action
  18. 18. © 2016 eMarketer Inc. Moving from predictive analytics to marketing  Every application of predictive analytics follows the same two-part structure: 1. Understanding what is being predicted 2. Figuring out what to do with that prediction
  19. 19. © 2016 eMarketer Inc. A standard predictive team requires three players* 1. A demand marketing expert 2. A data scientist 3. A technologist *They all need to communicate well
  20. 20. © 2016 eMarketer Inc. Putting the pieces of the predictive puzzle in place  Marketers need to know what type of business problem they are trying to solve to take action  Figuring out the business case will kick off the process
  21. 21. © 2016 eMarketer Inc. Predictive marketing can be used to improve the funnel at every stage 43% of US B2B marketers used predictive analytics to get insights about where prospects are in the sales funnel Source: 6sense and OnTarget Consulting & Research, April 2015 26% of marketing executives in North America said that a benefit of predictive marketing was better funnel conversions Source: Forbes Insights, April 2015
  22. 22. © 2016 eMarketer Inc. Primary objectives for predictive spanned across the customer funnel  The major objective, at 33%, was customer acquisition  At 17% each: – measuring behavior and insights – ad/campaign effectiveness – calculating and improving lifetime value – retention
  23. 23. © 2016 eMarketer Inc. Applying predictive marketing at every stage of the funnel  Finding new prospects  Lead scoring  Lifetime value of current customers  Personalization  Sales/channel support  Recommendations Awareness Consideration Purchase Loyalty Advocacy
  24. 24. © 2016 eMarketer Inc. Finding new prospects 51% of US B2B marketers used predictive analytics to find new prospects Source: 6sense and OnTarget Consulting & Research, April 2015 37% of marketing executives in North America used predictive marketing technologies to find new prospects Source: Forbes Insights, April 2015
  25. 25. © 2016 eMarketer Inc. Kasasa uses predictive marketing for pre-funnel scoring “They use predictive modeling to score potential buyers before they enter the funnel. If a bank doesn’t have the right combination of attributes like, for example, specific turnover rates, profit margins or number of customers, it’s eliminated. But prospects with a high predictive score are then proactively marketed to, because the model found they are most beneficial to talk to and more likely to convert.” —Phil Winters, Author, “Customer Impact Agenda: Doing Business from the Customer’s Perspective”
  26. 26. © 2016 eMarketer Inc. Lead scoring  B2B marketers can use predictive models to score leads to determine which individuals have a higher propensity to convert  Experts note this is the most common use case  Still, only 7% of B2Bs used predictive lead scoring
  27. 27. © 2016 eMarketer Inc. Getty Images scores leads with predictive to prioritize sales efforts “Using custom-built predictive indicators, we can take a set of 10,000 new leads that we’ve identified and then sort them in priority order based on the data that is available to us, and then use a predictive model to understand which leads are more likely to convert. … Sales can understand which leads have the highest propensity to buy. That information allows them to prioritize their efforts.” —Jason Widup, Senior Director, Demand Generation and Marketing Operations, Getty Images
  28. 28. © 2016 eMarketer Inc. Increasing customer lifetime value 32% of data management professionals worldwide used predictive analytics to predict lifetime value of each customer Source: Experian Data Quality and Dynamic Markets Ltd., Dec 2014 14% of marketing executives used predictive marketing to forecast and minimize churn within current accounts Source: Forbes Insights, April 2015
  29. 29. © 2016 eMarketer Inc. Major US wireless carrier uses predictive to understand the value of its B2B customers  Predictive models help the carrier acquire companies  In the funnel, it determines which customers will have the highest lifetime value – add more lines – upgrade to higher data buckets – add more premium devices
  30. 30. © 2016 eMarketer Inc. Getty Images predicts churn within its current accounts to minimize cancellations  When the predictive engine detects a decline in usage or another attribute associated with churn, the machine flags that account  This triggers a sales or marketing action to prevent the loss
  31. 31. © 2016 eMarketer Inc. Predictive techniques for personalization still have a way to go  While 41% used predictive to accelerate personalization, only 12% said predictive analysis was an essential criterion for personalization success  Personalization might be the end goal, but it is a strategy of predictive that needs refinement
  32. 32. © 2016 eMarketer Inc. A shortcoming to predictive personalization is the lack of a human touch “Most marketers want to hit the ‘easy’ button, but marketers need to tailor the message and be more empathetic. The problem is that empathy is not something that predictive analytics—the way it’s being sold today—is doing at all. It doesn’t provide you with empathy to understand the situation and the disposition of who you are talking to.” —Tim Hayden, Vice President, Marketing, Zignal Labs
  33. 33. © 2016 eMarketer Inc. HP employs predictive personalization through recommendations in partner channels  Partner channel Sales Central uses predictive to tailor solutions to each third-party channel partner or reseller  The hub delivers personalized suggestions for more successful campaigns and sales tactics for each partner  Then, personalized recommendations provide a tailored campaign or piece of content  This isn’t a direct-to-customer approach, but overlaps with two other essential uses of predictive marketing technology: sales support and recommendations
  34. 34. © 2016 eMarketer Inc. Measuring Predictive Marketing’s Value
  35. 35. © 2016 eMarketer Inc. Predictive marketing is seen as moderately valuable Extent to which investments in intelligent software, like predictive, are delivering expect business value for worldwide executives: Exceeding: 16% Expected value: 33% Some value: 39% Underperforming: 8% Source: Economist Intelligence Unit (EIU), sponsored by Accenture and Pegasystems, April 2015
  36. 36. © 2016 eMarketer Inc. How impactful is predictive marketing?  Just under half of B2B marketing decision-makers said predictive analytics had a very high impact on their business  Over one-third (36%) said there was considerable impact  13% cited some impact  Only 5% claimed to see little or no impact
  37. 37. © 2016 eMarketer Inc. Benchmarking predictive vs. nonpredictive determines effectiveness  55% of US B2B marketers who used predictive said their strategy was effective, compared with 18% who didn’t use predictive  Dell uses A/B tests and compares the results to see predictive’s effect
  38. 38. © 2016 eMarketer Inc. The most common metrics used to measure the success of predictive marketing included:  customer retention rates  customer value  cost per lead  projected ROI  total conversions
  39. 39. © 2016 eMarketer Inc. Predictive is not perfect … but it can still work  Data-derived predictions will never be 100% accurate all of the time  This isn’t science fiction or a crystal ball  Predictive equips marketers with information that they need to be smarter and more efficient
  40. 40. © 2016 eMarketer Inc. Current State of B2B Predictive Marketing Adoption
  41. 41. © 2016 eMarketer Inc. Predictive tech firms say the tipping point is now While only 31% currently used a predictive analytics tool, 54% were likely to invest in predictive analytics in the next 12 to 36 months. Source: 6sense, April 2015 38% planned to significantly increase the role of predictive analytics in the next year. Source: Lattice, Oct 2015 68% believed predictive marketing would be key to the marketing stack. 47% were investigating how to use predictive, and 25% were currently using it. Source: Everstring, Sept 2015
  42. 42. © 2016 eMarketer Inc. Sources other than vendors tell a different story Tactics that occupied vs. will occupy time and resources in 2015 and 2016 2015 2016 Predictive modeling 44.4% 44.4% Source: IAB Data Center of Excellence and Winterberry Group, January 2016
  43. 43. © 2016 eMarketer Inc. Why such a discrepancy?  Yes, predictive vendors might have a self-serving reason to be biased …  … but the more likely scenario is that predictive techniques can be bundled into larger marketing automation tools  Thus, predictive marketing’s adoption might be much larger than we think, because the capability might be folded into other marketing tech products
  44. 44. © 2016 eMarketer Inc. Predictive undercover in Google Analytics  Google Analytics offers predictive capabilities without actually labeling them as such  The Smart Goals feature uses machine learning to identify which website visits are most high-value and have a higher propensity to convert  Google doesn’t call Smart Goals predictive because many marketers using it might be turned off or intimidated by words like “predictive” or “machinery”
  45. 45. © 2016 eMarketer Inc. 49% expected growth of predictive intelligence, according to marketing leaders in the US Source: Salesforce, Jan 2016 38%of marketing executives worldwide said predictive analytics will have the biggest impact on marketing companies by 2020 Source: Economist Intelligence Unit (EIU), April 2016 Predictive is booming today, and likely tomorrow
  46. 46. © 2016 eMarketer Inc. Predictive will be here for a while and has a long way to go “As investors continue to pump funds into predictive vendors and technology, the capabilities will mature very rapidly. We are in the early stages right now, but predictive marketing isn’t going anywhere just yet.” —David Rabb, Principal, Marketing Technology and Analytics, Raab Associates
  47. 47. © 2016 eMarketer Inc. Key Takeaways  Predictive models, built from past customer touchpoint data, guide marketers by estimating which actions are most likely to pay off in the future  Using this and other data allows for more efficiency at all points of the marketing funnel  Measuring ROI can be a challenge, but benchmarking past performance will indicate if the method is adding value  B2B companies are slowly adopting predictive marketing and using it within their marketing technology stack  It remains uncertain whether this is the year predictive marketing goes mainstream
  48. 48. ©2016 EverString Predictive Marketing Making Marketing More Relevant June 2016
  49. 49. ©2016 EverString Predictive marketing starts with Audience Selection Audience Selection is the process of using data to identify the most relevant prospects… So you can market and sell to the right prospects, even if they are not in your funnel
  50. 50. ©2016 EverString Focus of predictive marketing to date Build Pipeline with Predictive Demand Generation Increase Conversion with Predictive Scoring Total Potential Market (all companies) Predictive Scoring prioritizes your existing funnel customer model A B C DTotal Captured Market within your CRM & marketing automation Predictive Demand Generation delivers net new, high value accounts
  51. 51. ©2016 EverString A breakthrough in predictive marketing EverString Audience Platform powered by the EverString Company Graph Uses semantic similarity to map the connections & similarities between companies Like the Google knowledge graph and Facebook people graph, but for B2B company data The EverString Company Graph maps the known universe of 11M B2B Accounts Total Potential Market (TPM)
  52. 52. ©2016 EverString An evolution in predictive marketing Data science helps identify and expand segments beyond the boundaries of your funnel, creating… Predictive Segments …which use semantic similarity to find look-alike accounts that are similar on specified dimensions These segments can be mapped to your products, territories, teams, events, campaigns and more EverString B2B Graph: known universe of accounts Total Potential Market Total Captured Market (TCM) Segment Segmentsegment Segment
  53. 53. ©2016 EverString An evolution in predictive marketing EverString B2B Graph: known universe of accounts Total Potential Market Total Captured Market (TCM) Segment Segmentsegment Segment Use cases to consider 1. Funnel Prioritization – use scoring to prioritize the prospects in your funnel 2. Segmented nurture – uses segments to optimize the nurture paths for your existing database 3. Multi-channel Programs – create and use a segment to market a campaign, program or event 4. New market expansion – identify a wholly new market to expand into and get accounts today 5. Territory Planning – create a segment for an individual territory for a rep or team 6. Account Based Marketing – identify target accounts and preform more directed campaigns
  54. 54. © 2016 eMarketer Inc. Learn more about digital marketing with an eMarketer corporate subscription Around 200 eMarketer reports are published each year. Here are some recent reports you may be interested in: Q&A Session Made possible by You will receive an email tomorrow with a link to view the deck and webinar recording. To learn more: www.emarketer.com/products 800-405-0844 or webinars@emarketer.com Jillian Ryan Predictive Marketing—Using Data Decisively at Every Stage of the Funnel  Predictive Analytics in B2B Marketing: Using Data Decisively, at Every Stage of the Funnel  B2B Sales Enablement: Driving Strategic Efficiencies Along the Path to Purchase  Marketing Technology: The Six Developments that Matter the Most in 2016  B2B Content Marketing in the US: Maximizing ROI and Cost-Effectiveness over Time

×