Using analytics to address high impact business priorities in hospitality

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Using analytics to address high impact business priorities in hospitality

  1. 1. © Absolutdata 2014 Proprietary and Confidential Chicago New York London Dubai New Delhi Bangalore SingaporeSan Francisco www.absolutdata.com April 30, 2014 Addressing high priority business issues in Hospitality through Analytics A wide range of examples show that the ROI on these efforts is high if done properly
  2. 2. © Absolutdata 2014 Proprietary and Confidential 2 Agenda Success Stories Analytics in Hospitality Marketing Mix Optimization New Hotel Decisions CRM Strategy Guest Satisfaction
  3. 3. © Absolutdata 2014 Proprietary and Confidential 3 CXOs are looking for Answers to Critical Business Questions Which new properties and locations should we invest in? How do we maximize REVPAR? How do we enhance flow through to the bottom line? How do we maximize customer value? How can we optimize Marketing ROI?
  4. 4. © Absolutdata 2014 Proprietary and Confidential 4 How do we maximize REVPAR? Which new properties and locations should we invest in? These questions can be answered better through analytics Concept Testing & Product Design  Understand central delivery capacity to markets  Assess impact of new branded and un-branded supplies Concept Testing & Product Design  Understand price sensitivity to demand  Forecast demand at various price points  Identify opportunities for higher opaque pricing Concept Testing & Product Design How do we enhance flow through to the bottom line?  Offer discounts only when there is a clear incremental impact  Move customers to profitable booking channels  Identify acquisition sources that bring in loyal, high value customers Concept Testing & Product Design How can we maximize customer value?  Measure Wallet Size & identify high value customers  Identify opportunities to engage, up sell, cross sell, prevent attrition and re-engage  Develop customer centric programs that drive revenue and engagement Concept Testing & Product Design How can we optimize Marketing ROI?  Assess revenue that is truly attributable to channels and marketing investments  Understand synergies, optimize spend and timing Business Questions How Analytics can help
  5. 5. © Absolutdata 2014 Proprietary and Confidential 5 ROI on these efforts is high - if done properly FIVE PRE-REQUISITES FOR SUCCESS  Senior management buy-in  Integration of disparate data sources with enterprise wide access  Test and learn culture  Collaboration across departments  Scalable insights delivery model
  6. 6. © Absolutdata 2014 Proprietary and Confidential 6 Market Mix Optimization Case Study Business Concern Complications  To find the True Value of reported impact in a multi channel, multi value ecosystem.  Same numbers were being reported by multiple platforms. The question was how to increase the effectiveness of the platforms  how do we optimize marketing ROI across online and off line channels? 30% 45% 60% 20% 100% ??? Resolutions Business Impact Phase 1- Holistic Base Model, Market Mix  Holistic approach incorporates all drivers with Appropriate level of modelling sophistication - OLS, HB Phase 2- Refinements, e.g. Structural Equation Models  Assess Synergies, Refine Attribution Phase 3 – Triangulation e.g. Cookie Data  Cookie data captures Unique ID activity and measure recency and frequency  Attribution’s % impact of each media channel drives daily proportions 53.1% 20.5% 14.1% 6.0% 4.1% 2.9% 0% 23% 45.6% 12.3% 8.8% 5.5% 4.5% 0.1% 0% 10% 20% 30% 40% 50% 60% Search TV Affiliates Display PR E-mail Print Primary Attribution After Secondary Attribution (Actual Contribution from Model) Impact of Secondary Relationship on Search= - 30% Impact of Secondary Relationship on TV= +25%
  7. 7. © Absolutdata 2014 Proprietary and Confidential 7 New Hotel Decisions Case Study Business Concern Complications  They also wanted to predict the wallets for stays at client’s hotels versus all competitors, with lower error rate (higher on accuracy)  The Client needed to take the decision of where to locate its new hotels, and their estimated ROI Resolutions Business Impact  Identified destinations which a customer is likely to visit based on his/her geographic and demographic profile – requires external data e.g. Visa to assess historical size of wallet  Overlaid the untapped opportunity (1-share of wallet) to identify opportunity spaces – using past stay behaviour from C360  Identified customers that are most likely to stay incrementally at the proposed new property – using behavioural and demographic information from C360. Measurement in solos gives wrong answers 30% 45% 60% 20% 100% ???  50% improvement in the accuracy rate in classifying guests into the High/Medium/Low Categories  The actual size of the wallet (point estimate) was predicted with a reduction in the error rate by 20%  The predicted point estimates target customers with the highest potential
  8. 8. © Absolutdata 2014 Proprietary and Confidential 8 CRM Strategy Case Study Business Concern Complications  In an ever increasing loyalty customer base, the client needed to scientifically decide which promotion should be sent to which customer, at what time, and using which channel Resolutions Business Impact  The loyal customers get blasted with promotions, while the non- loyal ones do not receive them  In the email world, the promotional & communication calendar is managed by moving the offer schedules, a process that does not truly address underlying conflict or optimize value.  Email is reaching Saturation Unified Metrics Financial Metrics Engagement Indices Quantifying Value Response Short Term Value Incremental Value Long Term Engagement Impact Optimize Algorithms Prioritized Contacts Constraints Go / No Go Decisions Test & Learn Enhance Offers Improve Targeting Enhance Business Rules  Synergies with other direct marketing initiatives to develop new vehicles  Combined Impact expected to exceed $100 MN over12 months
  9. 9. © Absolutdata 2014 Proprietary and Confidential 9 Guest Satisfaction Case Study Business Concern Complications  Satisfaction Scores were Dropping for a lot of client branches. They wanted to know why, and ways to mitigate it Resolutions Business Impact  51% guests retained by implementing the findings  40% improvement in customer satisfaction PROPERTY LEVEL ANALYSIS DATABASE Internal Database (Customer mix, Staffing Levels) Survey Information (Satisfaction and Loyalty scores) Trade Audit Data ( Competitor syndicated data, relative satisfaction scores) Data sources disparate from each other  Specific focus areas were identified and shared with branch managers to – Help them manage their assets better – Prioritize key action points to improve customer satisfaction Best Better Good Average Low  Each property was moved from its current performance band to next higher band  Multiply the target movements with pre- determined %increments
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