Artificial Intelligence (AI) enables marketers to understand the sales cycle along with correlating the already set strategies and spending to sales results. AI-driven insights are all set to assist the business in developing data-driven insights so that marketing and sales can collaborate to convert more of the potential leads. Marketing is more analytics and quantity driven than ever before, the complete real-time capture of the data many marketers have selected their best metrics when it comes to building a complete data-driven model. Marketing leaders are focusing on data, specifically metrics and KPIs, to track and why they fluctuate. The bottom is that machine learning and Artificial Intelligence (AI) are the technologies that marketing leaders and their teams need to excel today.
Some of the best marketing leaders balance the quantitative intensive nature of running marketing with quantitative factors that would make the companies brand and customer experience unique. With more insights from the data that can relate to how various prospects makes a decision when, where, and how they buy, the leaders can bring a new level of intensity into driving the complete outcomes. A clear condition of this can be seen in the recent Forbes Insight and Quantcast research; the study had concluded that AI enables the marketers to increase sales to 52 percent, increase in the customer retention up to 51 percent and have a successful new product launch for 49 percent. AI is making a solid contribution to improving the lead generation process, persona development, segmentation, pricing, and service. Most of the top-performing companies are more than twice as likely to be using AI for marketing according to the Adobes latest Digital Intelligence Briefing. Retailers are investing $5.9 Billion this year towards the AI-based marketing and customer service solutions to improve shoppers buying experience according to the IDC. Financial services, along with marketers, lead all the other industries in AI application adoption with 37 percent currently using them today. Sales and marketing teams are most collaborate using the Configure-price-quote (CPQ) and marketing Automation AI-based applications with many of the sales leaders even predicting AI adoption will increase by 155 percent across sales teams over two years.
Below are the 5 data points that provide insights on how AI is transforming the marketing
1. AI in Sales- 21 percent of sales leaders rely on AI-based applications for decisions making
Sales leader predicted that their use of AI would increase by 155 percent over the course of next two years, sales leaders predict AI will reach critical application performance requirement by 2020 when they expect that they would be using this technology. Marketing and sales are relying on AI-based marketing automation, configuration price quote, and intelligent selling systems that will improve the revenue over the course of next two years. According to the survey, marketing automation is at 104 percent two-year growth plan while partnering relationship management (PRM) at 95 percent.
2. AI will be seeing a significant amount of adoption
Businesses that are hovering between $500 million to $1 Billion are leading when it comes to the number and depth of AI adoption use cases. Just over 52 percent of small businesses with sales of $25 million or less are using AI for predictive analytics for improved customer insights. It’s also important to note that small companies are leaders when it comes to AI spending at 38.1 percent to improve the marketing ROI by optimizing the marketing content and timing.
3. Current AI Users- 22 percent of the enterprises are using AI-based applications
Currently, there are 22 percent of the marketers who are using AI-based applications with an additional 57 percent are planning to use it in the next two years. There are nine dominant use cases that the marketers are concentrating on today that range from personalized channel experiences to programmable advertising and media buying to the predictive customer journey and real-time next best offers. Marketers are using the complete data in an assortment way such as personalized channel experience, personalized overall customer journey, automation, and social media interactions, and predictive journeys.
4. Content Personalization and predictive analytics
Content personalization and predictive analytics gained from customer insights are the two main areas CMOs are mostly prioritizing to improve the AI spending. The CMO study found that B2B service companies are the top user of AI for content personalization almost in the cases of 62.2 percent. The B2B product companies are using the AI in the augmented and virtual reality, facial recognition and visual search more than any other business types. Predictive analytics for customer insights is applicable for 56.5 percent CMO plan, targeting decision is used by 49.6 percent of AI CMO plan and customer segmentation for 40.9 percent of CMOs.
5. Audience Targeting- 81 percent of the marketers are either planning to or are using AI in audience targeting this year
Around 80 percent of the enterprises are planning or using AI for the audience segmentation. EConsultancy’s study found that marketers are enthusiastic about the AI’s potential increase in marketing effectiveness along with targeting the tracking progress. For almost 88 percent of the marketers that were for the goal achievement.
Marketers and businesses agencies are most comfortable with AI-enabled bid optimization for media buying, followed with mitigation. They are currently differing on creating ad inventory selection and optimization with marketing teams often that get into opting to use their analytics and reporting instead of relying on the agency AI methods. Around 82 percent of the businesses are looking to improve the customer experience that will be contributing to AI adoption. As the businesses are finding the use of AI technology in marketing solutions, they are aggressively stepping in the data gathering and analytics part of using the data. Many marketing leaders believe that the next step for AI development would be real-time analytics.
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