Predictive marketing is a data science-enabled AI or machine learning model that forecasts the accurate performance of future campaigns based on historical data of campaign results. The digital explosion has transformed the way marketing channels operate, analyze, target, and position their products. Marketers who had a misconception about the growth and use of digital advertising, in the field of marketing and communications, should think about the potential of predictive analytics-enabled automated marketing.
Digital advertising channels leverage the applications of data science to exact the information to measure the accurate performance of enterprise ad campaigns, promotions, social postings, or video content so that companies can create engaging and compelling content that attracts their consumers. The limitation in data analytics can be overseen with the adoption of predictive marketing that changes the enterprise’s post-campaign optimized data insights to pre-optimize campaign execution. The platforms like Instagram, Amazon, and Pinterest, are evolving as digital dashboards for brand advertising. One million new users are joining youtube every year and they are active users of Instagram, and half of them adopt affiliate marketing and 20% of them will be affiliating Amazon products. According to GlobalWebIndex, 26% of internet users searched for products on social media last year and is expected to grow 5 times by 2025.
Predictive marketing is currently not used universally as it is supposed to be used. But the early users of it are driving a competitive advantage over others. The prototype for Predictive marketing is automated email marketing. In the last two years, companies deployed predictive marketing had maximized revenues through marketing consumer-engaging information, based on individual consumer historical data. This means marketers can optimize their campaigns for anticipated results, rather than performing post-campaign analysis.
The five key factors that are driving Predictive Marketing
1. Social networks penetration
Today’s marketers are researching innovative ways to reach their consumers. Technologies like AI, the internet of things, and virtual reality are unfolding and redefining marketing practices. The evolution of social networks is driving new consumers from various networks. Amazon Alexa, Spotify, Netflix, and other apps are providing an advantage to promote and place their products at the top of the consumer’s mind. It is predicted that every year 1 million new users are searching for brands on platforms like Instagram, youtube, etc. This penetration of social networks helps in better brand placements.
2. Micro movements
Micro movements define the where, how, why, and what movements of consumers. For example, if a consumer search for a smartwatch, its price, discounts, etc by entering various queries, the data is recorded to predict the consumer’s preference level which may generate unique leads. By analyzing these movements of the consumer, the brands can offer customized products and services to their consumers. The consumer movements include: go, know, do, and buy.
Without automation, the desire to detect and implement micro-movements is not possible. Predictive analytics adds an advantage in forecasting consumer intentions before they show interest in purchases.
3. Validating consumer data
The transparency of consumers’ data is no longer stronger with the increased mobile-based app service. These data inputs are generated and analyzed by every enterprise so that they can protect their consumers from choosing other offers in the market. With predictive analytics, the enterprise can forecast the consumers who are about to churn in real-time, and by providing customized services or offers the enterprise tries to retain its consumers.
4. Campaign optimization
Meeting ROI in digital campaigns nowadays has become difficult due to an increase in the presence of brands online. With the increase in the percentage of people using active social accounts and consumers becoming open about their preferences, the brands try hard to reach their consumers to stay ahead of their competitors. With predictive analytics based on data-driven insights about different market segments and target audiences, the future campaign can be redesigned and rescheduled to meet the enterprise’s primary goal of conversion.
5. Budget constraints
Ranging from digital advertising pop-ups to customized recommendation posts or videos, companies are spending billions on promotions. Predictive analytics can drive better results with customized short-period ads that reduce the cost spent on CPC or PPC-based advertising. Through predictive marketing, an enterprise can optimize advertising campaigns automatically with the help of other technologies, which reduces the time spent by advertising managers and teams for an optimized result.
Predictive marketing solves the limitations of digital advertising by predicting the real-time value insights of consumers. Optimized digital campaigns can generate a maximum value of output with minimum cost digital advertising campaigns. The future of marketing is unfolding various techniques to leverage current and upcoming technologies to maximize the market growth of every enterprise by addressing their unique target audiences’ future needs or unlimited wants.
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