Connect 2017 by Full Contact: Condensed Notes

The following are my notes from the Connect 2017 Conference put on by Full Contact. It was very insightful.
Base decisions on data to avoid marketing to people that are not interesting and nurturing those who are interested and building more human to human connections by personalizing the experience so customers want to express your brand.
  • Gathering Data
    • Why
      • Gaining insights into how you can nurture customers to high intent to purchase
    • What
      • Machine Data
        • Time
        • Location
      • Personalized data
        • Influencers
        • Values
        • Causes
      • Actual Customers
    • How
      • Focusing on actual customers establishes a real ‘intent to buy’ that can be examined
      • Disparate data sources
        • time and location help layer data  
        • Collect from a wide variety of data sources and expect non-conformity
          • can be as simple as a document or post or as complex as a aggregated list from a 3rd party service
        • Company touchpoints
          • map every touchpoint
          • list expectations at every touchpoint
          • customer value alignment at each touchpoint
          • “What do the customers avoid?”
        • Customer events
          • can be small like purchasing a product or a related dependent product
          • can be large like banquet or 5k
          • “What effect are the customers trying to cause prior to the event?”
  • Analyzing Data
    • Why
      • Anticipate needs to provide better customer service by understanding what customer is trying to do and what stands in their way
    • What
      • Customer Personas
      • Customer Journeys
    • How
      • Create Customer Persona to gain allies
        • Create a hypotheses about “why a customer converted?”
          • Understanding the answer to this question is the a shared interest between the company and customer and the base of the relationship
          • This defines a problem and a solution
          • Improve predictive model by reviewing hypothesis
        • Use the data to answer the questions:
          • “What do customers have in common?”
          • “How do customers want to be treated?”
          • “Why did customers like these events?”
      • Personalizing Customer Journey to anticipate needs
        • List customer events on timeline to map actual journey
          • “What shared interest was served by converting?”
          • “What customer events occurred prior to converting?”
          • “What are the customer’s needs during these events?”
          • “What was the context of the event?”
        • Build optimal journey
          • “How does this touchpoint serve the shared interest?”
          • “What are the needs at the touchpoint?”
          • “How do we exceed expectations at the touchpoint?”
          • What kind of Ads would “speak to the customer” because they are personalized?
          • Plan how you’re going to end the conversation 
      • Layer data
        • spend time with the data
        • don’t make customer irrelevant in the mix
        • Approaching data with a specific question is easier
  • Using Data
    • Why
      • Can not be customer centric without data and building human to human relationships will make customers want to express your brand.
    • What
      • 360 view of customer at every touchpoint
    • How
      • Touchpoints
        • Have a 360 view of customers at every touchpoint
          • Focus on personalized interactions by using data
          • CRM
          • Have the most relevant and up to date data
        • Control how the event ends
          • Always end amicably
        • It’s not about wowing 100% of the time, it’s about the little interactions
        • Consistently be better than average at every touchpoint
        • Augment both analogue and digital touchpoints
        • Do not act without ‘proof of life’ in persona
          • Build the relationship by starting with the shared interest
          • Don’t market to people who are not interested
          • Ask how to solve the personas’ problem
          • Do not try to make them say “yes,” but rather “that’s right”
      • Embrace a Data Culture
        • Use a Knowledge Management System
        • Document the customer experience
          • Update personas and journeys with new data
          • Data created by humans is awful; data created by machines is more reliable
            • remember, location and time are key to layer data
          • Negative feedback is still data
          • Triggering events at touchpoints can be a source of data
          • Progressively collect data
            • don’t create barriers to sign up with data collection
        • Data Sanitation
          • Remove and fix bad data like duplicates and typos
          • Consistently prune data like emails (bad emails will decrease reputation)
      • Inbound efforts
        • Not knowing who the person is a bad customer experience
        • Respond quickly to social media interaction
          • Resolve issues quickly
      • Outbound efforts
        • Never ask the customer to do work
        • A/B testing to limited audience
        • Promote through past customers
          • anticipate their needs at touchpoints and make them feel special
          • help past customers get more value out of product 
            • follow up if their questions are not answered in knowledge base
          • Proactively seek positive (5 star) rankings
            • ask past customers for reviews

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