Más contenido relacionado

Presentaciones para ti(20)

Similar a LOCALOGY ENGAGE 19: AI’s Impact on the B2B Customer Journey(20)


Más de Localogy(20)


LOCALOGY ENGAGE 19: AI’s Impact on the B2B Customer Journey

  1. Ai’s Impact on the B2B Customer Journey Proprietary & Confidential. Inc. ® Dalia Asterbadi
  2. An organization’s ability to learn and translate that learning into action rapidly is the ultimate competitive advantage” Jack Welch
  3. The Way People Buy & Their Loyalty Had A Lot To Do With The History Of Business Economics
  4. Voice Of Customer was At Core Of Our Business Process
  5. 100
  6. Prospecting Qualifying Nurturing Closing Managing Scale Visibility KPI’s Metrics Gating Automaton Scoring Content
  8. Your customer is informed. Your customer lives in an experience economy. Stuff happens everyday. Business needs to adapt.
  9. KNOWN UNKNOWN Social response • Liked on FB • Tweets about experience • Posts on SC or IG See digital ad • Impressions and clicks • Publisher site • Campaign Search • Search words • Referring URL • Site Activity Social Activity • Who they’re following • # of followers • Likes • Micro moments Personal information • Name, Address (Geo) • Email Address • Social handles Social Insights > Brands followers > Geo Location > Trends > Demographics See TV Ad • Impressions • Show • Campaign Decision-Making The Impact Opportunity Spotting Removing Blind Spots
  10. Nurturing Closing Value Creation Absolute Dynamic Process – Driven Metrics Closing Turning Data into Wisdom Behavior – Driven Metrics WOO Event Sales Gates Relationship Equity Scoring + Consider email open rate into email success rate
  11. Meet FBID 410483897077279 410483897… just liked your post on Facebook and the only information you know about 410483897… is that he just liked your post on Facebook. Do you know what to do next? Don’t just Count Things.
  12. His name is John He liked this post and he is new to the community John is a foodie, Especially with Thai and Indian food. He is a designer and connects with UX people. Would you feel confident to make your next move? Could you : 1. Align John to his journey position? 2. Identify value creation moments to meet his goals? 3. Optimize in real-time across your organization? Removing Blind Spots empowers authenticity & moments related to bsuiness outcomes. John was a customer over 3 years ago. No assigned rep. We first engaged with John 2 years ago He just responded to Stephen King promotion from Amazon
  13. Value CreationSales Gates Relationship Equity AI can help with WOO (window of opportunity)
  14. A.I is only as good as your business health KPI Evaluation: Sales Engagement Response time Application Completeness Persona/Target Competitive Takeout Why Blind Spots Matter Leads Opportunities Closed metrics indicate fail is here Use Case | Journey Process + Sales Success
  15. purpose Building a relationship goes beyond formally known ‘touchpoints’ To keep the attention of your customer understand your customer’s true identity PLUS Solve attribution problems from complex data solutions In a timely manner Your Journey to the power of n Discovery WOO Brand CUSTOMER EXPERIENCE Augmented Intelligence Customer-Driven Journey Model AudiencePersona
  16. purpose Identifying the Behavior & Playbook Activation BUYINGLIFECYCLEBYCUSTOMERSTAGE Reducing the average time to purchase with augmented intelligence targeted media and build awareness and loyalty in the customer lifecycle Customer Stage – Buying Behaviors • New Customer – Looking for education on their purchase and validation from the brand to make the right decision • Swing Buyer – Trial moments, reacting to peers, they make room for desire through unique content and seeking an emotional high purchase • Loyal Buyer – Amplifying Intent and strive to be first in trial and share their experiences with others Use Case | Buying Behavior + Market Insights
  17. purpose Do you know your customer? Use Case | Optimizing Sales & Marketing Effort
  18. purpose Find the data you need Use Case | Marketing Campaign Effectiveness Demographics Age Cultural Ethnicity Gender Location Language Job Role Expertise Current Status Engagement Inactive/Active Customer Since Log periods Recent activity NPS Segment Persona Recent Actions Life Events Personal Work Company Performance New/Shuffle Network trends Topics of Interest Personal Amplification Digital Breadcrumbs socialDNATM Trending Topics Brand Affinity Content Relevance New Networks Social footprint Recent Locations Presence & Persona Engagement Score Personalization at Scale Requires Hyper Segmentation & Awareness
  19. Tapping into the Tech Demographics Gender, Region, FanRankTM Sentiment & Content Relevance Reactions & impact on your brand - Negative, Neutral & Positive Topic Analysis Automatic classification of related topics including company news, StockRankTM Links & Embedded Social Data Analyze URLs shared or commented on specific criteria Engagement Valuation Engagement levels are reviewed to determine opportunities Text Analysis Privacy-safe aggregate analysis of text Persona Classification Qualitative attributes like presence, Intent, behavior & affinity Digital Asset Reference Quantify digital assets to prioritize pattern discovery Beyond regression….
  20. Brand Equity & Valuation Breaking Down Journey with AI BRAND • PRODUCT MEDIA • ACQUISITION MARKETING • Social SALES VELOCITY Content & Media Analysis Segmentation & Personalization Prospecting & Opportunity Management Authentic Word of Mouth Brand Reputation Brand Governance Overall Community Development Audience Segment Verification Content Discovery & Strategy Persona Creation Media Engagement Targeting Industry Benchmarking Brand Affinity Segments &campaign optimization Influencer Discovery Data Enrichment Sales Signals Risk Management/Competitive Intelligence
  21. Identifying AI Investment Effectiveness • Velocity of Metric Accessibility • Uncovering meta-level characteristics to segments • Increased Decision Making • Improved Accuracy & Optimization • Removing Bias (Journey-Exit) • Dramatically changing KPI of value
  22. What is the ultimate experience I am delivering? What passion points & exposure created engagement of the experience? How is motivation harnessed in my organizations sales and marketing process? Operations Brand Creation Data Modeling Why are we developing these programs? How does my talent represent this? How to I Adapt without shifting? Do I create value at every stage of the experience? Questions Your Business Should Answer
  23. Dalia Asterbadi @D_Asterra
  24. An ad agency wanted to improve social engagement and presence for a snack brand around sporting events. With topic data they found that many of the assumptions around audiences and engagement were incorrect: ๏ Assumed 18 to 24 year old men. It actually turned out 35 - 66 year old women were engaging. ๏ Expected pre-game excitement to peak just before game time. It really peaked almost 6 hours earlier. ๏ Thought most games were watched with friends. Turns out most are watched with families. Longitudinal study would allow these assumptions to be tested for a variety of sporting and non- sporting events and also surface previously unsuspected brand connections. Recommended Actions ๏ Use accurate knowledge of audience engagement to create more relevant messaging and campaigns. ๏ Target messages to audiences with better timing, to match true engagement patterns prior to game. 18-24 MALE 35-66 FEMALE ASSUMPTIONS Vs. DATA FRIENDS FAMILY Challenging your assumptions
  25. An ad tech company wanted to improve performance for a campaign on Facebook for a national music festival. Topic data identified audiences that were more and less likely to engage with content and help target promotion: ๏ Identified that Women 25-34 from Kentucky, Indiana, Michigan & other states over-indexed in music genre engagement. ๏ Identified that Men 18-24 from California under- indexed in the music genre engagement. ๏ Identified a range of related interests, websites, retailers and broadcasters that could be used for targeting. This campaign had been nine months in the planning before topic data was brought in. If topic data had been available all the way through that process, then content could have been tailored better throughout. Recommended Actions ๏ Diverted spend from under-indexing to over-indexing demographic groups improving engagement rates and driving a 17% increase in video completion rates. ๏ Identified artists and potential co-marketing partners to inform future campaigns and tailor content. CALIFORNIA 18-24 KENTUCKY 35-44 AVERAGE ENGAGEMENT Driving engagement on content
  26. A TV show producer needed to make more informed decisions around advertising and social content, as well as casting decisions for future seasons. Based on topic data producers were able to better target content and inform casting decisions: ๏ Identified the characters gaining the most engagement on Facebook and then identified variations by gender, age and state. ๏ Identified the scenes & storylines that drove most engagement over the season. ๏ Identified potential actors for an upcoming season that resonated with their core target demographic. Using topic data throughout the life-cycle of a season would not only inform the current season, but also subsequent seasons and other shows. Recommended Actions ๏ Tailor sponsored updates to feature an image of the most engaging character for each demographic group. ๏ Casting was also able to evaluate new actors that already resonate most with the TV show’s core demographics. SCENE A SCENE B SCENE C SCENE D Developing your product
  27. #Customer Experience
  28. Developing trusted insights. Always make best effort at every stage of journey to answer the elements that remove blindspots. WHO WHAT WHERE WHEN HOW WHY Verifying Audience Targets. Based on our content, what key personas are there. What detailed socialDNA attributes can be then re-targeted in media. Optimize Distribution based on key channels that impact brand. nfluencers real affinity and the identity of those engaged. The impact of amplified content
  29. What do you see?
  30. The Data Evolution & Data Science Proprietary and Confidential Applied Value Unapplied Value