AI Best Practice

Nothing is better than things that are proven to work.  Andyou can find them here. First, an overview of the use of AI in marketing practice – and  the best tools with impact right after.

From our 2021 study on AI in marketing ⤵.

(Representative survey of 158 marketing managers in D-A-CH, 2021)

Everyone is talking about AI and its use is slowly increasing

A large proportion of the marketing managers surveyed attach great importance to AI in business and marketing - which has increased significantly since 2018; companies that use AI in marketing are satisfied: The use of AI in marketing is at least ONE driving factor for success. Nevertheless, the use of AI in marketing still remains at a comparatively low level.

There is a clear discrepancy between "wanting" and "doing"

Despite these increases, only about 8% of respondents also use AI in marketing on a daily basis. As in 2019, this is not a significant increase over 2018. Still, 91% say AI should be used more in marketing - this figure has continued to rise since 2018.

In the survey, evidence can be found of five reasons for hesitant deployment

Their own knowledge of AI is low and attitudes toward AI are changing positively overall, but there are still skeptics. In addition, AI perceptions appear to differ between managers and employees. Operationally, the use of AI is difficult because there is sometimes little focus on data - there are few resources in some teams to analyze data. This leads to little real-world experience with AI. This is one reason for the hesitant attitude toward AI use.

Managers' need for information on AI is still very high in all core marketing tasks

Across all core marketing tasks - consumer insights, strategy/planning, product/service, advertising/sales, and performance management, respondents say they subjectively have too little knowledge and would like more information on the use of AI in these areas.

Although attitudes toward AI are changing positively overall, there are still skeptics.

Segmentation of respondents further reveals six different AI manager types; Opportunists (AI for short-term marketing effectiveness enhancement) and Strategists (AI as an advantage for future development of the whole company) are most common; Compared to 2018, Skeptics (basically negative attitude) decrease significantly, Strategists increase significantly; but Skeptics still account for about 10% of respondents. Skeptics are fundamentally negative about AI.

Managers tend to see higher benefits and different team challenges in AI than employees do

Managers tend to rate the importance of AI higher than their employees. They tend to assume that competition is no better and see challenges not in job loss but in AI training. The team members are quite different.

In 36 out of 100 marketing departments, less than 5% of employees deal primarily with data and insights

A focus on the intensive use of own data by own experts does not seem to exist in more than one third of the marketing departments. The department seems to be either becoming more specialized in core marketing topics only (which doesn't require data specialists) ... or becoming full-service marketing providers including data analytics experts directly on the marketing team.

Nearly half of respondents already using AI in marketing use standalone solutions; only 15% of AI tools are fully integrated

AI still seems to be relatively little integrated into standard processes and established as an everyday tool.

(Representative survey of 158 marketing managers in D-A-CH, 2021)

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