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McKinsey: AI Will Have the Most Impact in Marketing

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A recent McKinsey study found that AI will have the most impact in marketing and sales, supply chain management, and manufacturing.

This conclusion was drawn by mapping traditional analytics and newer artificial intelligence techniques, and the problems they can solve to more than 400 specific use cases in companies and organizations across 19 industries.

This is exciting news for marketers and business professionals alike. Below, we’ve highlighted the key industries and use cases AI can heavily influence, as well as McKinsey’s recommendations for getting started. You can find the full report here.

Realizing AI’s Full Potential

As stated above, artificial intelligence has the power to tremendously impact several fields, including marketing and sales. However, in order for that potential to be reached, McKinsey shares that companies will be required to implement AI in areas where they can effectively create the most value.

The implementation of AI in the travel industry, for example, can more than double what is achievable through traditional analytic methods, amounting to between seven and 12 percent of total revenue for the industry. A specific example McKinsey references is how Hawaii’s state tourism authority, in conjunction with a major online travel company, uses facial recognition software to monitor travelers’ expressions through their computer webcams to deliver personalized deals.

Not sure what that means for your business? McKinsey recommends following the money. If you’re in an industry where marketing and sales are the main driver of value, such as consumer packaged goods, banking, retail, telecommunications, high tech, travel, insurance, and media and entertainment, AI can help.

Personalization Opportunities

Two of the marketing and sales areas McKinsey identifies where AI tools can be used to immediately improve performance are customer service and personalized marketing.

Personalization can be a company’s competitive advantage by using customer demographics, past transaction data, and social media monitoring to offer “next product to buy” recommendations. For example, Amazon uses AI to send daily emails with product recommendations and Netflix uses AI to curate your viewing homepage with tv shows and movies you’re likely to be interested in. In both cases, these companies have seen a substantial increase in their rate of sales conversion thanks to AI.

For customer service, call center management can also be streamlined using artificial intelligence. For example, a combination of chatbots and speech recognition can be used to identify if customers are frustrated talking to a machine and forward them to a human customer service assistant, instead. Together they can offer more efficient processing and a more seamless customer experience.

Affected Industries

In terms of specific industries, McKinsey found that consumer industries such as retail and technology will see more potential from AI than others. Because artificial intelligence requires a vast amount of clean and organized data, the frequent digital interactions between brands and customers in these industries generate larger datasets for AI to pull from.

Ecommerce, specifically, will see huge impacts from the utilization of AI because of the ease of which they collect customer data. Metrics like click data and time spent on page are immensely useful in personalizing products, prices, and promotions for individual customers.

Getting Started With AI

For companies looking to adopt artificial intelligence, McKinsey offers some next steps.

First, as you begin your search for AI technology, you will be bombarded by businesses offering “AI solutions.” Before testing these out, McKinsey recommends taking a step back and approaching your search more holistically.

Create a prioritized portfolio, instead, that looks to answer which use cases within your organization have the potential to drive the most value. Consider which of these can actually be deployed at scale across the enterprise.

McKinsey also suggests looking closely at the “first mile” and “last mile.” What has to be done to acquire and organize data and efforts, as well as how will the AI output be integrated into the people and processes of the organization (workflows, sales managers, procurement officers)?

Photo by Matt Barrett on Unsplash.

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