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Marketing analytics


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Marketing analytics enable CMOs to make data driven decisions

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Marketing analytics

  1. 1. NASSCOM Marketing Analytics Report Operations in San Marketing Research 250+ employees Francisco and Advanced Analytics and AbsolutData Proprietary and Confidential
  2. 2. Sections Marketing Analytics Overview Trends in Marketing Analytics Key Challenges for Industry Players Way forward 2
  3. 3. Marketing analytics enable CMOs to make data driven decisions Illustrative Sales & Marketing issues addressed leveraging analytics Bottom line impact Top line impact Price & Sales and Product Branding CRM Promotions Distribution Development Who are my How should Who are my How should What new Strategic customers? I price the best I distribute products to products? customers? products? introduce? What are What should How can I What trade What their needs? the retain & incentives features to promotion grow them? should I include? strategy be? run? How much What base What offers How much Which should I price should should I run to distribute variants spend on I charge for to win-back through the should I branding? my product? customers? channels? introduce? What What How do I Which trade Should I message promotions maximize incentives introduce Tactical should I should I run response to work best? newer pack communicate this year? campaigns? types? ImpactSOURCE: AbsolutData Analysis 3
  4. 4. Marketing analytics solutions continue to evolve Illustrative Evolution of Marketing analytics solutions Descriptive Prescriptive Executive Summarize large “volumes” Analyze past & large Incorporate high Business of data to understand past “variety” of data to “velocity” data to self- Challenges better predict future better correct & execute better Brand Tracking Market Mix Modelling CPG Market Performance Sentiment Analysis Shopper Insights Dashboarding Travel Promotion Tracking Travel Wallet & Share Contact Optimization B2C & Loyalty Programme Promotion Performance Customer Experience Hospitality Performance Forecasting Management Store Profitability Analysis Market Basket Analysis Location based Marketing Retail Category Management Sales Forecasting Product recommendation B2B Sales Force Effectiveness Customer Lifetime Value Technology Customer Account Dashboards Price Optimization / ConjointSOURCE: Company Websites; AbsolutData Analysis; 4
  5. 5. Indian industry has an opportunity to grow to over $1.2 BN at 25% CAGR by 2020 Illustrative Marketing Analytics potential for India (in $ billions) 1.4 1.2 1.2 1 0.8 0.6 0.4 0.2 0.2 0 2012 2020SOURCE: Industry Reporting; NASSCOM KPO Report; AbsolutData Analysis 5
  6. 6. Value chain of analytics work being delivered from India High High-to- Medium Medium- Low Illustrative Medium to-Low Solutions Global Adoption Current State of Indian service providers Real Time Digital Feeds Services being delivered leveraging existing End User App User Developed Models products developed in mature markets Interactive Dashboards Limited product development Market Assessment Leveraging / modifying algorithms and Modelling CRM methodologies developed in mature markets Marketing Effectiveness Initial investments in R&D have happened Metrics Reporting Being provided extensively as service Reporting/ Dash boarding Product development still in its infancy Visualization Ad-hoc analysis Data Integration Mature players with extensive experience Data Management ETL services are present Digital Data Integration Providers leverage extensive experience of delivering IT services over the years Data Sourcing Already well entrenched established players Infrastructure Data Warehousing in this space Tools and Technologies Although it is ubiquitous across geographies, Organizational Development India still enjoys a cost advantageSOURCE: AbsolutData Analysis 6
  7. 7. 2 Trends in Marketing AnalyticsTrends Implications for Players Marketing Analytics engagements are likely to increase in number (more clients) and size (organization wide implementation) Marketing Analytics is top on the agenda of Players need to focus their sales efforts to CXOs, in addition to BU heads CXOs Solutions are no longer only judged on technical parameters but also on business impact potential Solutions need to adapt to the new realities of larger volume, velocity and variety of data CMOs are dealing with increasing that are increasingly available in marketing complexities in the current environment Players need to develop solutions that are simple to understand and use, to ensure wider adoption within organizations Solution scope is now enterprise wide and that are consistently applicable across business units across regions Marketing Analytics solutions now need to Solutions need to be embedded in IT platforms that integrate well with existing client integrate with organization wide functions applications Players need to upgrade their implementation skill sets across consulting, large scale project implementation & IT Solutions need to be re-worked ab-initio to ensure optimal results Newer digital platforms are increasingly Players need to up-skill their IT & data handling capabilities becoming relevant for marketing decisions Players need to be flexible in leveraging the various technology platforms as the landscape is still evolving Solutions are increasingly expected to be intelligent and actionable at the hands of non- Marketing Analytics is increasingly being technical end-users leveraged real time for execution support Solutions need to be more plug ‘n’ play and embed well in existing client IT systems Solutions need to self correct with minimal human intervention 77
  8. 8. 3 Challenges in Marketing AnalyticsChallenges Opportunity for Players Disaggregate the analytics role into 3 sub-components that are widely available in India – Players are unable to scale up their Business / Domain specialists, Technical experts and Data scientists / engineers analytics capabilities due to a global Increase the employable talent for Analytics by increasing or improving skills in areas like shortage of deep analytics talent consulting skills and business / domain understanding Delivering analytics solutions globally needs Players need to build a well coordinated global delivery model with a mix of onsite talent (for a balance in solution consistency across solution localization) and off-shore talent (for solution consistency) regions while retaining a degree of Players should invest in building on-site / near shore delivery centers to house talent localization sourced locally Players need to invest in employee engagement beyond rewards and focus on meeting Industry faces a high cost in attrition as individual’s aspiration on accelerated career development / progression analytics is a combination of complex skills Players need to reduce the time & cost of on-boarding by setting up learning academies that are hard to find and take time to build (similar to what IT players have done) Players need to build productized solutions, specific to industry verticals, that are proven Clients are demanding “plug’n’play” and can be configured easily solutions that can be setup faster and are Players can increase solution fit by co-creating solutions with clients as well as by more cost effective incorporating the learning / best practices from their various other experiences Players need to be flexible to adapt to the various BIG data technologies while the industry Leveraging BIG data requires players to continues to evolve have new skills especially in technology and Players need to invest up-front in building new frameworks / solutions to incorporate BIG business integration data into the current traditional solutions 88
  9. 9. Top predictions of changes in Analytics for next 5 years Predictions for Future Illustrative Predictions Illustrative Examples Deep Analytics talent will increasingly Facebook is already hiring psychology PhDs into leverage two types of talent - “Computer their Analytics unit to better understand science” PGs for machine learning individual’s interests and actions in order to Talent solutions and “Psychology” PGs for appropriately tailor their solution offerings tailoring solutions that cater to individual needs / preferences “Self-healing / Machine learning Google cloud based machine learning API helps technologies will become an indispensible businesses adopt machine learning as a part of Solution part of mainstream solutions deployed” their enterprises “Clients needs of one-stop, end-to-end IBM has been increasingly consolidating tools solutions will trigger greater consolidation such as Cognos and SPSS to broaden its Eco in the industry” analytics portfolio and bundle them along with its System IT product / services offering. They are also focusing on big insights and big streamsSOURCE: Company Websites; Industry Articles 99