automation solutions<\/a>.<\/p>\nCampaigns that are more effective and efficient: <\/u>Successful campaigns are highly targeted, ensuring that the right message is delivered to the right audience at the right time. Organizations can now identify website visitors and turn unknown prospects into known leads. One can segment the leads on multiple parameters such as behaviors, demographics, etc. to craft personalized lead cultivating campaigns.<\/p>\n
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Organizations can now more\u00a0track and identify website visitors and even turn a few unknown prospects into known leads. Once these customer buckets have been identified, the teams can segment the leads on multiple parameters such as behaviors, demographics, etc. to craft personalized and automated lead cultivating campaigns.<\/p>\n
Conserve Resources and Be More Creative: <\/u>Marketing automation tools help users save time, and possibly money with more informed decision making. Businesses are also empowered to channelize their efforts in producing more relevant, creative, and compelling content and outreach campaigns.<\/p>\n
Repeatable processes facilitate re-using marketing collateral saving manhours and costs. This frees up some budgets to make a bigger noise in the market and increased ROI.<\/p>\n
Driving better customer experiences<\/strong><\/p>\nThe new age consumer demands customized purchase and buying experiences. This leads to less obvious sales tactics that can be deployed by the marketing teams and more thought leadership to convince consumers. The end goals of all marketing campaigns may culminate in sales, but there are other objectives that are key, and these include creating better engagement.<\/p>\n
The responsible side of automation<\/strong><\/p>\nMaximization of Profit: <\/u>Must brands avoid the temptation of profits at the consumer\u2019s cost? Can marketing automation create a state of guilt?<\/p>\n
It\u2019s understood that businesses maximize profit at the maximum point to what a potential consumer is willing to pay. Today, ML-based prediction algorithms can decipher fairly accurate estimates of a consumer's willingness to pay.<\/p>\n
Businesses like Uber supposedly incorporate machine learning to set prices based on demand, time, and routes. Ride histories of customers can personalise prices even further. Such situations can lead to businesses seeking advantage by making consumers pay prices as close willingness to pay or even marginally higher.<\/p>\n
Losing out on autonomy: <\/u>While being autonomous in choices, autonomy requires privacy. A lack of privacy can make consumers predictable. Algorithms to predict buying behaviour more easily. Research indicates that consumers choose less preferred options to re-establish their sense of autonomy if its known that algorithms can predict their behaviour. Businesses can frame them such that they don\u2019t threaten consumers\u2019 perceived autonomy.<\/p>\n
Unfair compensation for personal data: <\/u>A consumer often undermines personal data while bartering it for goods or services as opposed to selling it for money. Consumers \u201csupposedly pay\u201d for free social media services with their personal data. Leading platforms use such data to make advertising profits. Such actions contribute to the extraordinary valuations of giant tech companies.<\/p>\n
Businesses stand a lot to gain from automation with benefits that are enticing for marketing teams. The planning and all the inputs that go into marketing initiatives can determine how big the success using marketing automation. A global artificial intelligence software market predicted to reach nearly 125 billion U.S. dollars by 2025 could mean fascinating times ahead with marketing automation.<\/em><\/p>\n\u00a0<\/em>The author Dhara Shah is Chief Marketing Officer at Allied Digital Services.<\/p>\n <\/p>\n\n
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