The Marketing connection
Data science can be leveraged to accurately predict the marketing strategy and actions that are bound to succeed at an organizational level. In other words, marketing decisions are driven by predictive intelligence. Be it analyzing multiple data points, finding correlations, or identifying patterns that may have never been noticed by marketing professionals, predictive intelligence is the driving factor. These insights help you determine customer attrition, retention, and potential customers as well. It can also tell you the minimum discount you would have to offer to win back old customers or even bring back customers who have left their shopping carts. All this without you having to churn numbers.
So, how can predictive analytics introduce added insight and clarity into your marketing decisions?
ACCURATE CUSTOMER BEHAVIOR PREDICTION
Customer intelligence is the key to better business. Reaching out to your customers across channels with the right message at the right time is possible through predictive techniques. Machine learning and artificial intelligence also helps marketers study customer behavior through patterns and similarities in the data. With the past purchasing behavior of customers, it is easy to determine their future purchases too.
With predictive modelling, marketers can also predict customers who are likely to leave and those who are ready to buy. Thus, so far as intelligent marketing strategies and informed decisions are concerned, predictive models are here to stay.
EFFECTIVE SEGMENTATION AND PERSONALIZED MESSAGING
Personalization matters and it goes beyond addressing customers by their names. Marketers face their share of challenges with customized messaging. There is either a lack of accurate data, not enough data or they simply can’t gain quick insights.
Whether it is for upselling, cross-selling, product recommendation, or reaching out to customers in real time, the next best logical step is machine learning and predictive technology because it enables automated segmentation for personalized messaging.
IDENTIFYING AND PRIORITIZING QUALIFIED LEADS
Customers with no inclination to make any purchases (known as unqualified leads) end up costing organizations time and money. Predictive modelling, algorithms, and identification patterns help marketers zero in on potential prospects who share similarities with existing buyers, thus maximizing opportunities for new sales.
Additionally, even if your business has limited funds, predictive analytics can help determine which resources to use at what time and give forecasts on high-value customers with the highest probability of making purchases. This ensures an optimized marketing spend.
Driving Growth through Smart Analytics
Big data and predictive analytics have risen to the top of the corporate agenda—for all the right reasons. In sync with each other, they promise to revolutionize the way companies do business, which involves establishing critical metrics and communicating ROI to the business. However, the challenge that most organizations face is the decision making around setting marketing budgets and spend allocation. Big data and analytics have been buzzwords for the last few years, but now the factors prompting the buzz are changing. With better data, sharper predictions, and improved ability to optimize, it is now even easier to make informed decisions and, in turn, generate better ROI. To become growth engines, organizations need to embrace smart analytics right away.
While gathering enormous amounts of data is a huge task in and of itself, being able to use it effectively is a different scenario altogether.
It empowers business leaders to make informed decisions by synthesizing the Art of Judgment and the Science of Data. We go beyond investing in the basic blocks such as analytics, discovery, and automation. With DecisionMinesTM, we leverage data to determine which pieces to actually gather and turn them into winning decisions.