3 Reasons Prescriptive Analytics is Changing Marketing
Prescriptive analytics — the new kid on the marketing block — builds on the foundation of descriptive and predictive analytics. As we explained in a recent blog post, prescriptive analytics goes beyond merely describing where a company has been and then predicting where it's going.
Prescriptive analytics leverages both descriptive and predictive analytics to offer solutions for getting your company where you want it to go. And that's the reason at least some experts believe that prescriptive analytics is the future of marketing.
Prescriptions from Predictions
Prescriptive analytics enables you to benefit from the best of both descriptive and predictive analytics, by predicting future trends based on past data and offering solutions to achieve desired results.
For example, prescriptive analytics can help your brand:
1. Decide what price points to offer and what segments of customers to maximize both company revenue and customer value.
2. Proactively manage your inventory and marketing campaigns based on anticipated demand for given products.
3. Target the optimal media for sending marketing campaigns, whether it's email, text, direct mail, or social media.
Prescriptive analytics works by applying machine learning to data from customer transactions, competitor behavior, and other sources. It provides value by giving recommendations for the next best courses of action to meet pre-defined goals, whether it's for revenue growth, customer retention, or other targets. Then by simulating those recommended actions, it determines their impact on your goal.
Adding to the power of prescriptive analytics, Ki also continually updates its suggestions as new data comes in, providing refreshed recommendations to you based on evolving circumstances.
For the individual marketer or marketing manager, prescriptive analytics offers three broad benefits that help drive widespread adoption of the technology.
1. It Takes the Gut Factor Out of Decision-Making
Marketers may have a wealth of experience to draw from when making decisions, including insights into how to reach prospects and craft just the right messages for customers to generate new opportunities. But those same marketers know that only reliable data can let them trust their instincts.
Analytics can help you make key determinations, such as whether a given group of customers will respond favorably to a given offer, or how customer receptivity will change in response to various competitor behaviors.
Prescriptive analytics uses your data from past customer interactions and other critical factors, and provides recommendations for moving the needle, based on insight gleaned from automated analysis.
For example, your gut instinct may tell you to coupon more heavily to increase customer loyalty, however, that is typically a short term solution. Prescriptive analytics may tell you, instead of couponing more heavily, target a specific group of customers with ads for clothing as that will have the biggest impact to their customer loyalty.
2. It Augments the Intelligence of Marketers
Prescriptive analytics enables you to combine data-backed solutions with the marketer's touch. For example, software like Ki can create dozens to hundreds of data-vetted strategies. But it's up to the marketer applying their domain knowledge to choose between them.
In other words, prescriptive analytics tools don't replace the expertise of marketing professionals. Instead, it helps you make better decisions by narrowing your choices and presenting the likeliest path to achieving defined goals, enhancing your own abilities with the power of artificial intelligence, based on up-to-the-minute data.
3. It Results in Customer-Focused Strategies
Prescriptive analytics allows marketers to do more on an individualized and more personalized basis than traditional marketing strategies have been able to do in the past. For example, AI-driven analytics can help marketers craft messages and offers for highly segmented groups of customers.
Such personalization leverages predictive analytics of past transaction data to predict what customers will purchase next.
The payoff for highly customer-focused marketing strategies is high. It cuts acquisition costs, boosts revenue, and makes marketing budgets as much as 30 percent more effective.
The Road Ahead
Given the benefits, it's no wonder that the 2019 CMO Survey from Deloitte, Duke University, and the American Marketing Association reported that spending on analytics as a percentage of marketing budgets would rise 61 percent by 2022.
Still, while prescriptive analytics is steadily making converts among marketing teams, challenges remain. These include:
1. Setting the marketing priorities that will benefit most from analytics.
2 . Finding the most effective use cases for it.
3. Getting buy-in from key stakeholders.
4. Ensuring that analytics has access to good-quality data.
Despite the challenges of this still-maturing technology, however, it's essential to get on the prescriptive analytics train now. And descriptive and predictive analytics aren't going obsolete any time soon, either. All three will have an increasingly important place in the your analytics toolbox into the foreseeable future, thanks to modern automated data analytics tools.
To learn more about Ki and how you can implement an AI analytics solution right now, request a one on one demo and start turning your data into action.
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