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Artificial Intelligence for Marketers

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Artificial Intelligence for Marketers

As a marketer, you know the importance of content. That’s not changing any time soon. Back in 2014, we saw content-first design hit peak momentum. Then mobile-first design came on the scene, which is still widely considered the best practice for digital marketing. Then, Google shifted the conversation toward experience. In 2017 Google CEO Sundar Pichai summarized the Google I/O keynote by describing, “An important shift from a mobile-first world to an AI-first world.” When Google announces a monumental move that impacts the core of its business, it’s worth paying attention.

AI is taking off.

Consider these stunning statistics:

  • 47% of business executives say they have embedded at least one AI capability in their business processes.1
  • 21% say they have embedded AI in several parts of their business.1
  • 30% say they are piloting AI.1

I hope your company can be counted in these ranks (if not, we’d love to help!). As we live into an AI-first world, it’s important to understand what it is and how it can improve marketing outcomes.

What exactly is AI?

For the purposes of marketing today, artificial intelligence is a way to outsource low-level, high-volume information gathering to a machine. It analyzes and organizes consumer behavior data and either provides actionable analytics (this person lives in Denver and is gluten-restricted), or acts on those analytics (here are gluten-free tortilla chips we are selling in your area). It uses deep learning to determine patterns and find meaning in them without human bias (and without costly, time-consuming human analysis).

  • Better Experiences: AI helps improve speed to market by simplifying key elements of the testing and development process. It can also help create unique, customized digital experiences by storing and reacting to website/app usage behaviors and consumer-provided information. 
  • Better Results: AI-driven campaigns are seeing new campaign revenue grown organically from positive customized experiences and higher customer engagement rates.

Sephora uses AI‌ to personalize experiences.

Sephora is a great case study demonstrating AI-driving customization in our omnichannel world. By connecting their digital and retail outlets, Sephora customers feel as though their needs and preferences are understood, and their recommendations reflect those preferences. As a result, they’ve seen an increase in consumer affinity and higher conversion rates.

Sephora website interface

How are they doing it? They’re investing in AI and partnering with personalization specialists such as Dynamic Yield. Dynamic Yield is an AI-powered service that provides customized product recommendations to customers. Since Sephora is all in on a personalized experience, they are leveraging machine learning (ML), which is one aspect of AI.

Sephora makeup slider

These ML algorithms weigh factors like location and previously viewed and/or purchased products (online and offline) to inform a personalized experience including product recommendations that match skin tone, promotional offers relevant to past behavior and availability based on consumer location. By incorporating AI into the shopping experience, Sephora saw an ROI of six times their financial commitment. This experience brings the right product at the right moment for each individual user. It optimizes the checkout flow and connects their brick and mortar stores to their online experience. That’s the power of an AI-first approach.

How can you use AI today?

  1. Recommendations—AI-powered content recommendations and personalized offers can help you get better at delivering what a user wants. AI will take everything you know about a user (browsing patterns, referral link, location, time) and curate recommendations. The more data you feed the AI, the better the recommendations.
  2. Software Testing—Testing is a crucial part of creating positive consumer experiences. It can also be time-consuming (and expensive) for developers to take on. AI-powered acceptance testing allows AI to check thousands of web pages to ensure visual consistency (think fonts, buttons, spacing, etc.) in a matter of minutes. Application programming interfaces (APIs) also flag bugs in high-volume digital projects that involve different applications, different browsers and/or different devices. In short, this helps more efficiently determine if websites and apps are going to work as they should wherever and however they are used.
  3. A/B Testing—AI-powered A/B Testing takes the intricacies of multivariate testing and incorporates smart changes faster than humans can. This kind of AI can experiment with hundreds of options and fine-tune website conversion. While it’s not autonomous (yet), in the hands of an optimization expert AI‌ improves conversion at a faster rate.
  4. User Testing—Unleash an AI to see user behavioral patterns you may be missing. People are fallible and sometimes biased in their analysis. AI‌ analytics even the playing field and remove opinion from the analysis.

What other cutting-edge tech should you be using today?

1McKinsey & Company, 2018

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