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Market Research V1 November 14, 2022

Objectives

1. Assess whether there’s need for our product and how big the potential market is.
2. Understand current process of video marketing personalization and the potentials of generative AI in the space.
3. Get a good sense for the competitors in the space and the products they are offering.
4. Determine who the potential users are for the product and, if possible, answer:
   • What are they trying to accomplish?
   • What pain points and motivations do they have?

01 The Demand for Personalized Video Marketing

Personalization in Marketing

• Personalization has long been norm in the marketing space and according to Salesforce’s Fourth Annual State of Marketing Report, 52% of consumers and 65% of business buyers will switch brands if the vendor doesn’t personalize communications.
  • As digital marketing becomes more competitive, there’s a shift towards hyper-personalization, which is done by creating custom and targeted experiences through the use of data, analytics, AI, and automation. Through hyper-personalization, companies can send highly contextualized communications to specific customers at the right place and time, and through the right channel.

Deloitte Report, “Connecting with Meaning: Hyper-Personalizing the Customer Experience using Data, Analytics, and AI”, pg 13

Trend Towards Personalized Videos

Video is one of the most popular and effective forms of online marketing content. A personalized video is any video content that’s customized and relevant to the target audience (prospects, existing customers, and influencers). Recently there’s been steady a trend towards engaging customers through personalized videos.

• Videos can 1-to-1 (made specifically for an individual) or 1-to-many (made to target a specific consumer group). Here are some different types of personalized videos used in marketing:

  

  Wyzowl, “The State of Video Marketing 2022”, pg 9

  • Sales Demo Videos - showcases how the product can work for each specific customer.
  • Explainer Videos - help customers understand the product in relation to their unique needs & picture how it could be applied within their actual life.
  • Thank You Videos - thanking customers for using a product to foster engagement/brand royalty.
  • Event Invite Videos - personal invite to upcoming company events.
  • Personalized Loyalty & Rewards Videos
  • Personalized Review/Celebratory Videos - celebrating customer wins (eg: fitness journey reviews and milestones)
  • New Product Feature Announcements

• What are some examples of successful personalized video marketing campaigns?

  • Facebook’s “Year in Review” - video highlights recaps from the user’s profile including photos, number of friends made, and important events.
  • Nike and the Outdo You with Nike+ (similar to FB’s “Year in Review”)

• How are personalized videos currently being created for marketing purposes?

  • Made by creating a video template onto which CRM (customer relationship management) data is integrated

02 Video Marketing and the Potential for AI

• *Hubspot “Video Marketing Starter Pack”
  • The Attract Phase
    • Videos in this phase: product explainer, intro, how-to, testimonial, vlog, brand play videos
  • The Engage Phase
    • If everything else was done right, this is where people will want to do a deeper dive
      • This is where you pose on social channels to drive lead generation
      • can be a sales-y video as long as its balanced out with authenticity on your site
    • Videos in this phase: webinar, Q&A/AMA, Tutorials, livestreams, Reels/Stories, UCG (User generated content), Product/Service Review
  • The Delight Phase
    • Create memorable content for prospects to share
    • Types of video: seasonal greetings, thank you videos, brand evangelism (testimonials), customer onboarding, nurturing, behind the scenes, customer support videos
• Most current personalization algos are designed for static cases with a “greedy objective” where the firm only focuses on immediate rewards, according to the AI and Personalization paper successful methods must be:
  • scalable
  • generalizable and robust to confounding
  • adaptive in real-time - made possible by leaps in computer power and data storage (pg 18)
  • dynamic or forward looking - account for interdependence between actions over time, capturing immediate and expected future rewards (pg 8)
• A possible framework for AI in marketing: