Raise your Brand's Analytics IQ with Salesforce Einstein
1 like539 views
The document presents an overview of Salesforce's capabilities in advanced analytics and AI for the retail and consumer goods sector, highlighting the importance of tailored brand experiences for consumer engagement. It emphasizes the critical role of analytics in enhancing customer satisfaction, improving marketing ROI, and driving sales performance across various stages of the consumer journey. Additionally, the text warns about potential risks related to forward-looking statements and the necessity for businesses to establish effective AI strategies and use cases to leverage data for better decision-making.
Raise your Brand's Analytics IQ with Salesforce Einstein
- 1. Gib Bassett, Retail and Consumer Goods Customer Success Director gbassett@salesforce.com Raise your Brand’s Analytics IQ with Salesforce Einstein Consumer Goods Industry Theater Session Wed., June 19, 1:30 pm, Lake Opeka Theater
- 2. Forward-Looking Statement Statement under the Private Securities Litigation Reform Act of 1995 This presentation may contain forward-looking statements that involve risks, uncertainties, and assumptions. If any such uncertainties materialize or if any of the assumptions proves incorrect, the results of salesforce.com, inc. could differ materially from the results expressed or implied by the forward-looking statements we make. All statements other than statements of historical fact could be deemed forward-looking, including any projections of product or service availability, subscriber growth, earnings, revenues, or other financial items and any statements regarding strategies or plans of management for future operations, statements of belief, any statements concerning new, planned, or upgraded services or technology developments and customer contracts or use of our services. The risks and uncertainties referred to above include – but are not limited to – risks associated with developing and delivering new functionality for our service, new products and services, our new business model, our past operating losses, possible fluctuations in our operating results and rate of growth, interruptions or delays in our Web hosting, breach of our security measures, the outcome of any litigation, risks associated with completed and any possible mergers and acquisitions, the immature market in which we operate, our relatively limited operating history, our ability to expand, retain, and motivate our employees and manage our growth, new releases of our service and successful customer deployment, our limited history reselling non-salesforce.com products, and utilization and selling to larger enterprise customers. Further information on potential factors that could affect the financial results of salesforce.com, inc. is included in our annual report on Form 10-K for the most recent fiscal year and in our quarterly report on Form 10-Q for the most recent fiscal quarter. These documents and others containing important disclosures are available on the SEC Filings section of the Investor Information section of our Web site. Any unreleased services or features referenced in this or other presentations, press releases or public statements are not currently available and may not be delivered on time or at all. Customers who purchase our services should make the purchase decisions based upon features that are currently available. Salesforce.com, inc. assumes no obligation and does not intend to update these forward-looking statements.
- 4. “Although many companies have successfully implemented data warehouses -- massive databases containing large volumes of historical data for analysis and reuse -- many more have struggled to do more with that data than run basic reports using simple tools.”
- 6. “The vision we have is the brand entrepreneurs with a creative on one side and a data scientist on the other, with their hands on the keyboard making things happen and creating things in real time.” P&G CMO Marc Pritchard, April 2018 “Imagine you had a magic 8-ball and you could ask it anything, what are the wicked problems you wish it would answer?” P&G Principal Enterprise Information Architect Terry McFadden, October 2016
- 7. Who cares about analytics? Your Retail Partners and Your Consumers...tailored brand experiences powered by analytics support retail partner success and helps win moments of truth with consumers The CDO…interested in how Salesforce’s advanced analytics and AI capabilities fit with current and planned data strategy and information architecture The Salesforce Administrator…interested in what use cases are possible within the platform to contribute to data driven success Customer and Consumer Insights/The BI Analyst…interested in the packaged and custom possibilities available in the Salesforce platform to support and enable for business users
- 8. Who cares about analytics? The Data Scientist…interested in access to data and a platform to demonstrate the meaningful impact of analytical work quickly for their organizations Digital and Brand Marketing, D-to-C E-Comm, and Consumer Affairs or Customer Service Leaders…collaborating with other teams to execute seamless consumer journeys Trading Partner Sales and Shopper Marketing Leaders...seeking a consumer-centric sales and promotional strategy to reduce dependency on discount based trade spend The Supply Chain Leader…wanting to improve efficiency and accuracy, plus greater synchronization with the demand side of the business
- 9. Understand your Analytics Opportunity 9 Data & Advanced Analytics: High Stakes, High Rewards, 2017 Only 13% of RCP executives believe that their advanced analytics strategy is well established and central to the overall business strategy.
- 10. Remember….AI is Analytics Notes from the AI frontier: Applications and value of deep learning McKinsey Global Institute – April 2018 Understand which use cases and domains have the potential to drive the most value, as well as which AI and other analytical techniques are needed to capture that value. This portfolio ought to be informed not only by where the theoretical value can be captured, but by the question of how the techniques can be deployed at scale across the enterprise.
- 11. Grade your company’s Analytics IQ?
- 12. Overcoming Barriers to AI Business Value Barriers When asked about top barriers to AI, enterprises cited finding use cases and defining strategy, security/privacy, risks and integration complexity. Nearly two of three organizations cited finding a starting point as a concern. Identifying Use Cases Look at how you are using technology today during critical interactions with customers — business moments — and consider how the value of those moments could be increased. The CIOs Guide to Artificial Intelligence, February 4, 2019
- 13. Pre-Shop Shop Post-Shop Your Consumer’s Journey #1 CRM Apps Community Cloud Marketing Cloud B-to-C Commerce Cloud B-to-B Sales Cloud Service Cloud Analytics Data Sources Salesforce Data Other Data Use Case DeploymentPackaged Custom • Einstein Apps for Salesforce Clouds • MyEinstein (Sales Cloud and Prediction Builder) • Einstein Analytics Platform • Einstein Discovery • Einstein Vision and Language • Unique models, scores, and attributes developed by your team • Delivered via APIs, Heroku PaaS ML Services, SI Partners Recalling Connections 2018: Analytics in the Service of Superior Customer Experience
- 14. Your Consumer’s Journey Consideration Pre-Shop Shop Post-Shop Browse / Buy Service / Referral Inside / Out View of Analytics Powering Customer Experience Your Goals Stimulate Demand Fulfill Demand Retain and Grow Relationships Improve Content Relevance, Marketing & Advertising ROI, Brand Value Improve Sales, Margin, Category Growth, Market Share, Channel and Promotional Performance Maximize Customer Satisfaction, Loyalty, Referral A Cyclical, Non-Linear Journey Metrics 1. How do analytics support this process in your company? 2. What use cases are in place? Could you improve? 3. Do you know how Salesforce can help?
- 15. Your Consumer’s Journey Consideration Pre-Shop Shop Post-Shop Browse / Buy Service / Referral Inside / Out View of Analytics Powering Customer Experience Out of the Box (OOB) Use Cases Your Goals Stimulate Demand Fulfill Demand Retain and Grow Relationships Improve Content Relevance, Marketing & Advertising ROI, Brand Value Improve Sales, Margin, Category Growth, Market Share, Channel and Promotional Performance Maximize Customer Satisfaction, Loyalty, Referral OOB Salesforce Cloud Analytic Use Cases A Cyclical, Non-Linear Journey Metrics Email Engagement Segmentation Email, Web & E-Commerce Product Recommendations Advertising Audience Insights Social Influencer Insights, Social Vision, Propensity to Escalate to Social Predictive Assortment Product Discovery Customer Self Service Predictive Case Context Impact on CX
- 16. Out-of-the-Box Analytics Use Case Summary CG Use Case Capability Cloud Main Stakeholder/s Business Outcomes Advertising Audience Insights DMP Journey Insights Marketing Media Leader and/or Agency Improve media spend return via lookalike audience targeting and engagement (both anonymous and known) based on unified view of prospects and customers across channels and devices. Customer Self Service Einstein Bots Service Customer Service, Support, Care, Consumer Affairs Leader Easily build, train, and deploy custom bots to serve more customers, more quickly, and improve case resolution times, agent productivity and customer satisfaction. Email Engagement Segmentation Engagement Scoring Marketing Digital Marketing Leader Predict whether customers are likely to engage with, convert, or churn from your marketing campaigns so that you can optimize audience planning and increase opt in relationship conversion, and campaign ROI. Influencer Insights Einstein Influencer Insights Marketing Social Media Leader and/or Agency Predict which followers on social media are the most influential for your brand or products so you can engage and turn them into evangelists. Predictive Assortment Predictive Sort Commerce E-Commerce or Digital Marketing Leader For D-to-C channels, predict and present the most relevant product assortments to customers to improve CX relevancy and sales. Predictive Case Context Case Classification Service Customer Service, Support, Care, Consumer Affairs Leader Predict the context of a case in advance so that agents can suggest the right solution to customers more quickly and improve customer satisfaction. Product Discovery Search Commerce E-Commerce or Digital Marketing Leader For D-to-C channels, predict the search terms that need to be added to ensure that shoppers always see the most relevant results onsite, convert more often, and return more frequently as a result. Product Recommendations for Email, Web and E- Commerce Einstein Marketing Cloud Recommendations and Commerce Cloud Recommendations Marketing and Commerce Digital Marketing, E- Commerce, Merchandising Leader For D-to-C channels, improve conversion and sales by using customer interaction and purchase history along with like-customer behavioral data to recommend next most likely product to customers across email, website and e-commerce channels. Propensity to Escalate to Social Social Studio Service Customer Service, Support, Care, Consumer Affairs Leader Predict the likelihood of a customer escalating a case to social media, so that you can pre-empt that decision with proactive support and mitigate potential viral consequences. Social Vision Einstein Vision for Social Studio Marketing Social Media Leader and/or Agency Detect images in social media channels to identify customers and manage brand perception. Review Later
- 17. Your Consumer’s Journey Consideration Pre-Shop Shop Post-Shop Browse / Buy Service / Referral Inside / Out View of Analytics Powering Customer Experience Use Cases Developed by Administrators and Analysts Your Goals Stimulate Demand Fulfill Demand Retain and Grow Relationships Improve Content Relevance, Marketing & Advertising ROI, Brand Value Improve Sales, Margin, Category Growth, Market Share, Channel and Promotional Performance Maximize Customer Satisfaction, Loyalty, Referral Use Cases Supported by Analytics Studio / Einstein Discovery A Cyclical, Non-Linear Journey Metrics Data Sources Salesforce Cloud Data Other Data Lifetime Value Segmentation Churn Risk Up / Cross Sell Predictive Next Incident Social Sentiment or Language Impact on CX
- 18. Admin or Analyst Created Analytics Use Case Summary CG Use Case Capability Cloud Main Stakeholder/s Business Outcomes Churn Risk Analytics Studio / Einstein Discovery + Next Best Action Service Customer Service, Support, Care, Consumer Affairs Leader For D-to C channels, predict the likelihood of a customer leaving so that you can intervene and improve retention. Lifetime Value Segmentation Analytics Studio / Einstein Discovery Sales, Service, Marketing, Commerce CX leaders across the customer journey For D-to-C channels, if managing your consumer records in Sales or Service Cloud, quickly derive moving lifetime value calculations for your customers to deliver a CX that maintains, improves and grows this cohort of high value customer relationships. Predictive Next Incident Analytics Studio / Einstein Discovery Service Customer Service, Support, Care, Consumer Affairs Leader Predict the likelihood of a customer experiencing an incident so that you can deliver proactive service to improve customer satisfaction. Social Language and Sentiment Einstein Platform Services Service Social Media Leader and/or Agency Use natural language processing to identify positive, negative, or neutral sentiments in social posts to prioritize brand responses. Up and Cross Sell Analytics Studio / Einstein Discovery + Next Best Action Service Customer Service, Support, Care, Consumer Affairs Leader For D-to-C channels, predict the likelihood of a customer or prospect purchasing a particular product, so that during customer service interactions, agents are able to position new products and services inline with customer acquisition and retention strategy. + Many more…(now with Tableau too!) Review Later
- 19. Your Consumer’s Journey Consideration Pre-Shop Shop Post-Shop Browse / Buy Service / Referral Inside / Out View of Analytics Powering Customer Experience Custom Use Cases Developed by Data Science or Partners Your Goals Stimulate Demand Fulfill Demand Retain and Grow Relationships Improve Content Relevance, Marketing & Advertising ROI, Brand Value Improve Sales, Margin, Category Growth, Market Share, Channel and Promotional Performance Maximize Consumer Satisfaction, Loyalty, Referral Example Custom Use Cases A Cyclical, Non-Linear Journey Metrics Data Sources Salesforce Cloud Data Other Data Integration, Data and Analytic Options Mulesoft Unique models, scores, and attributes developed by your team or partners Datorama Heroku PaaSEinstein Analytics Digital Field Service (IoT) Demand Forecasting / OSA Promotion and Pricing Effectiveness Product Quality and Yield Impact on CX Tableau
- 20. Data Science or Services Partner Created Analytics Use Case Summary CG Use Case Capability Cloud Main Stakeholder/s Business Outcomes Demand Forecasting / On Shelf Availability Mulesoft, Analytics Studio / Einstein Discovery, Vision + potentially custom work via Python, R or using ML libraries + TABLEAU Sales + Heroku PaaS and other data sources Sales Leadership, Demand Planning Minimize out of stock conditions with insights that leverage data across the demand chain, including orders, shipments, point of sale, loyalty, digital marketing, pricing, social media, weather and others. Digital Field Service (IoT) Mulesoft, Analytics Studio / Einstein Discovery, Vision + potentially custom work via Python, R or using ML libraries + TABLEAU IoT Cloud, Service + Heroku PaaS and other data sources Customer Service / Field Maintenance Leaders Leverage data generated by sensors and machines in the field, such as refrigeration, transportation, and vending to identify and resolve issues, proactively schedule maintenance before breakdown while minimizing service costs, maximizing uptime and ensuring customer satisfaction. Product Quality and Yield (IoT) Mulesoft, Analytics Studio / Einstein Discovery, Vision + potentially custom work via Python, R or using ML libraries + TABLEAU IoT Cloud, Sales and Service + Heroku PaaS and other data sources Sales, Production and Quality Leaders Ensure quality, and maximize yield and machine uptime, through the analysis of sensor, video, and other data sources such as satellite. Proactively monitor conditions and identify when intervention is merited to improve outcomes (especially helpful for agribusiness). Promotion and Pricing Effectiveness Mulesoft, Analytics Studio / Einstein Discovery + potentially custom work via Python, R or using ML libraries + TABLEAU Sales + Heroku PaaS and other data sources Channel Partner Sales, Trade Promotion and Shopper Marketing Leaders If managing customer (retail) Point of Sale and promotional data in Sales Cloud or also using Heroku PaaS for high volume data management, leverage the power of AI to analyze and predict promotions that yield the highest margin and volume. Leverage D-to-C and PII marketing data, social channel, weather, economic and other sources to test and improve results with retail partners. + Many more… Review Later
- 21. Your Consumer’s Journey Consideration Pre-Shop Shop Post-Shop Browse / Buy Service / Referral Your Goals Stimulate Demand Fulfill Demand Retain and Grow Relationships Improve Content Relevance, Marketing & Advertising ROI, Brand Value Improve Sales, Margin, Category Growth, Market Share, Channel and Promotional Performance Maximize Consumer Satisfaction, Loyalty, Referral A Cyclical, Non-Linear Journey Metrics B-to-B-to-C Analytics at Work in Consumer Goods Email Engagement Segmentation 1.Develop Engagement and Social segmentation on digital consumer PII using data across the journey to inform advertising audience selection – for Brand Management, Media and Agencies Advertising Audience Insights Social Influencer Insights, Social Vision, Propensity to Escalate to Social Social Sentiment or Language
- 22. Your Consumer’s Journey Consideration Pre-Shop Shop Post-Shop Browse / Buy Service / Referral Your Goals Stimulate Demand Fulfill Demand Retain and Grow Relationships Improve Content Relevance, Marketing & Advertising ROI, Brand Value Improve Sales, Margin, Category Growth, Market Share, Channel and Promotional Performance Maximize Consumer Satisfaction, Loyalty, Referral A Cyclical, Non-Linear Journey Metrics B-to-B-to-C Analytics at Work in Consumer Goods 2.Align media and digital marketing with trade promotion spend to focus on acquiring and retaining more highly engaged consumers to support shopper marketing – for Trade, Sales and Shopper Marketing Leaders Promotion and Pricing Effectiveness Email Engagement Segmentation Advertising Audience Insights Social Influencer Insights, Social Vision, Propensity to Escalate to Social Social Sentiment or Language
- 23. Your Consumer’s Journey Consideration Pre-Shop Shop Post-Shop Browse / Buy Service / Referral Your Goals Stimulate Demand Fulfill Demand Retain and Grow Relationships Improve Content Relevance, Marketing & Advertising ROI, Brand Value Improve Sales, Margin, Category Growth, Market Share, Channel and Promotional Performance Maximize Consumer Satisfaction, Loyalty, Referral A Cyclical, Non-Linear Journey Metrics B-to-B-to-C Analytics at Work in Consumer Goods 3.Ensure coordination among Marketing, Trade Promotion and Supply Chain to reduce OOS – for Supply Chain Leaders Demand Forecasting / OSA Promotion and Pricing Effectiveness Email Engagement Segmentation Advertising Audience Insights Social Influencer Insights, Social Vision, Propensity to Escalate to Social Social Sentiment or Language
- 24. Your Consumer’s Journey Consideration Pre-Shop Shop Post-Shop Browse / Buy Service / Referral Your Goals Stimulate Demand Fulfill Demand Retain and Grow Relationships Improve Content Relevance, Marketing & Advertising ROI, Brand Value Improve Sales, Margin, Category Growth, Market Share, Channel and Promotional Performance Maximize Consumer Satisfaction, Loyalty, Referral A Cyclical, Non-Linear Journey Metrics B-to-B-to-C Analytics at Work in Consumer Goods Demand Forecasting / OSA Promotion and Pricing Effectiveness Email Engagement Segmentation Advertising Audience Insights Social Influencer Insights, Social Vision, Propensity to Escalate to Social Social Sentiment or Language Consumer Insights Data Sources Salesforce Cloud Data Other Data Integration, Data and Analytic Options Unique models, scores, and attributes developed by your team or partners Heroku PaaSEinstein Analytics MulesoftDatoramaTableau
- 25. Expected Business Improvement Source: McKinsey Advanced Analytics
- 26. Your Consumer’s Journey Consideration Pre-Shop Shop Post-Shop Browse / Buy Service / Referral Homework Your Goals Stimulate Demand Fulfill Demand Retain and Grow Relationships Improve Content Relevance, Marketing & Advertising ROI, Brand Value Improve Sales, Margin, Category Growth, Market Share, Channel and Promotional Performance Maximize Customer Satisfaction, Loyalty, Referral A Cyclical, Non-Linear Journey Metrics Use Cases Owners Related Systems Current Results To request, email gbassett@salesforce.com