Posted by Shivali Anand
March 16, 2022 | 4-minute read (677 words)
Return on investment is one of the most challenging issues that small company owners confront, particularly when it comes to marketing. Marketing initiatives are expected to help produce profit and maximize revenue.
Artificial intelligence has already transformed many industries, including marketing. AI has proved that marketing professionals can establish loyalty through enhanced user experiences and personalized messages by offering more significant insights into customer behavior, gleaned through AI.
Using the power of deep learning, AI can make real-time, data-driven choices and its one-of-a-kind predictive skills may help organizations be more compassionate. AI has enormous promise to increase brand engagement, improve suggestion viability and streamline purchase procedures.
In recent years, the use of AI in marketing has exploded. Here are three ideas to help marketers better understand what AI can accomplish for them:
• AI can better identify and target consumers by combining deep learning and big data strengths.
• Voice recognition and object identification are two examples of innovative technologies that allow businesses to communicate with their consumers more meaningfully than ever before.
• AI in marketing allows businesses to communicate directly with customers, turn their data into valuable assets and generate a blueprint for better serving them in the future.
How can AI help you boost your ROI?
In these five areas, analytical insights and sophisticated analytics can dramatically increase your marketing ROI:
1. Audience segmentation:The better you can segment an audience into distinct groups with comparable expectations, requirements and habits, the more effectively you may design and cater to focused client segments. Even though manual segmentation can be used, AI-assisted strategies allow you to study an almost infinite number of variables (far beyond trade zone statistics and basic demographics). They do so with far more fairness and accuracy, identifying patterns that humans may be unable to do to spot or simply overlook.
This data can assist you in identifying categories where upselling, conversion, cross-selling and other retention methods appear to be more likely.
2. Predicting customer intent:Artificial intelligence (AI) enables you to operate on more than just hunches. AI can employ predictive analytics to include advanced tools like sentiment analysis into every encounter with a user, interpreting innovative cues like tone of voice, volume and cadence, among hundreds of other data points. It becomes simpler to forecast future actions and tailor your marketing campaigns as you better understand prior consumer behavior.
3. Personalizing offers and other messages:According to a Harris Poll/RedPoint Global study released in 2019, "63% of consumers agree that personalization is now part of the standard service they expect" and "37% of consumers indicated that they will no longer do business with a company that fails to offer a personalized experience." Despite this, customization remains a difficulty for 44% of marketing professionals.
According to an Epsilon survey, "80% of consumers are more likely to make a purchase when brands offer personalized experiences."
Marketers may customize content based on precisely categorized data for a seamless experience that makes consumers feel appreciated, heard and understood by using AI in their marketing activities.
4. Multichannel attribution: In multichannel attribution, every consumer device, channel and touchpoint, as well as their journey, is assessed and graded in terms of the chance of conversion in comparison to other touchpoints. One issue with this method is the massive amount of data collected as close to real-time as feasible to improve outcomes and the following investment.
This is where artificial intelligence (AI) and data analytics come into play. Multichannel attribution enabled by AI gives a level of big-picture clarity beyond human capabilities, clarifying the marketing effort's direction and increasing the reliability of the data produced.
5. Predicting customer turnover rate: According to ThinkJar, a Customer Strategies advising and research think-tank, just 1 in 26 unsatisfied customers (less than 4%) will complain; the rest will simply churn. Using algorithms that can scan millions of pieces of data, AI can avoid customer churn (or attrition) by identifying high-risk categories and adapting marketing efforts appropriately. According to another study, boosting client retention rates by only 5% may increase earnings by 25% to 95%.