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Marketers: Would you add machines to your personalization team?

By Matthew Wakeman | July 22, 2021 | 0 Comments

MarketingContent Marketing and ManagementCustomer ExperienceCustomer Understanding and Marketing ExecutionDigital Marketing Strategy and ExecutionMarketing Data and AnalyticsMarketing Technology and Emerging Trends

Personalization continues to be a hot topic for marketers (subscription required)

Here’s the challenge though – it’s becoming more and more difficult to use simple rules and business context to make personalization decisions. Why?

  1. Marketers continue increasing the number of channels they use to engage with prospects and customers.
  2. As a result, they also increase the size and diversity of their marketing technology stacks (many of which include more than 60 technologies – subscription required).
  3. An explosion of possibilities for personalization – too many for standard rules – coming from the growth in channels, technologies, and content.

Marketers are still staffing their personalization teams with data scientists, CX designers, content creators, and others.

Marketers organize teams in different ways:

  • Internal Product lines (e.g., lines of business)
  • External customer personas/segments (e.g., Tier 1 loyalty customers)
  • Internal Technology (e.g., specific platform or skill; data scientists, CX designers, content creators, etc)
  • External experiences/channels (e.g., website, email, etc)

And while they’re bringing on technology platforms to manage most of this, team roles have largely been limited to people. Now, machines are starting to do more than orchestrate personalized journeys and prescribe next best actions.

Machines are starting to enrich product and content assets with key metadata.

Machines solve two problems with content assets:

  1. Explosion of content variants without the corresponding explosion of people to catalog and classify them
  2. Need to maintain and continuously re-align the ontology of metadata that supports those assets.

So now we have machines doing several jobs in a typical personalization workflow:

  1. Classify and add attributes to all of the content asset variants (ongoing, asynchronous work)
  2. Maintain the attribute ontology for those assets (ongoing, asynchronous work)
  3. Develop the models that identify “next best actions” for prospects and customers (asynchronous work)
  4. Orchestrate marketing delivery technologies to get those “next best actions” in front of the right audiences. (synchronous/real-time work)

Marketers, would you add machines to your personalization team?

  • What’s spectacular about adding machines to your team?

  • What’s spooky about it?

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