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mim903959
Mar 03, 2022
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It's no surprise that AI technology is all the rage in almost every marketing department these days. According to Phone Number List Forrester's AI Adoption Report, 94% of respondents believed that AI-powered marketing would be very valuable to their business. Yet more than 67% of respondents also said they have concerns and barriers to AI adoption. AI and Machine Learning for Marketing Download Premium Resource - AI and Machine Learning for Marketing The guide aims to help businesses of all sizes apply to their marketing, focusing on artificial intelligence. All companies can now use the services we recommend to implement machine learning. The guide explains why, how with an actionable and practical approach. Access AI and Machine Learning for Marketing The benefits of AI technology in marketing are clear: AI can automate many processes to save a lot of time. It can also use big data collection and analysis for effective targeting and forecasting. It can even engage with customers through machine learning-powered chatbots for higher conversions and better experiences! So why aren't the Phone Number List other half of marketing departments still using this kind of amazing technology? Let's talk about 4 of the biggest obstacles to the optimal use of AI. 1. Translating knowledge into strategy According to the Forrester report mentioned above, one of the biggest concerns most marketers have about AI adoption is the complexity of the technology. 35% of marketers said they simply didn't know enough about AI to consider using it for their strategy, and 29% thought it would be too difficult to implement in their campaigns current. Concerns Hindering AI Adoption However, simply citing a lack of knowledge is certainly not a valid excuse for postponing AI adoption. Big Data is growing at an alarming rate, and not making it part of your sales and marketing strategy could be a step towards obsolescence. As data flows become even more complex and the information needed to Phone Number List drive personalization strategies becomes more available, the more it will be necessary to translate information and knowledge into a successful strategy. Take the example of CRM (customer relationship management) systems. ,
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