In the year 2013, an eCommerce juggernaut launched drones—Octocopters— that could feasibly be used as autonomous delivery vehicles. They did not stop there. The following year, they came up with a robust system of delivering products to customers before they place an order, called Anticipatory Shipping: taking the online buying process to the proverbial ‘next level’.
Tapping the buy button and getting the product in just a few hours or minutes would be a huge breakthrough for the no.1 eCommerce player in the world: Amazon.
Predictive modeling is one of the major techniques behind Amazon’s algorithm-based system. This system helps to connect dots that reveal meaningful customer insights based on their previous orders and other factors, including time on site, duration of views, links clicked and hovered over, shopping cart activity and wishlists.
The magic of predictive modeling in the marketing dashboard is not just limited to the eCommerce industry, instead, it can be a huge game-changer in transforming many organizations of any size across industries.
What is Predictive Modeling?
Predictive modeling is a commonly used statistical technique to predict future behavior. Predictive modeling solutions are a form of data-mining technology that works by analyzing historical and current data and generating a model to help predict future outcomes.
Imagine, predictive modeling as—Precogs—mutated humans from Minority Report, who could “previsualize” crimes by receiving visions of the future, reducing the murder rate to zero. Similarly, predictive modeling has the capability to reduce the churn rate close to zero.
3 Benefits of Using Predictive Modeling in Dashboards to Empower Decision Making
Today, enterprise businesses collect huge amounts of customer data from disparate sources. Customer data has the potential to make or break any business. Such is the power of data! Unfortunately, in most cases, businesses are not tapping into this untapped potential because they are only gleaning insights from their dashboards, just using data analytics, which is able to visualize the data based on the past trends and unable to deliver a futuristic view of the data.
Predictive modeling, on the other hand, makes use of the latest innovations in machine learning and data visualization to enable you to visualize the impact of your marketing activities, perform “what if” scenarios to predict outcomes, and identify the probability of visitor engagement through predictive scoring on dashboards.
The ability to forecast the future, based on the past with predictive analytics can help organizations to increase profits and reduce costs.
1. Know Your Customer’s Next Step
“The aim of marketing is to know and understand the customer so well the product or service fits him and sells itself.”~ Peter Drucker
Your organization has a certain budget and you want to use it to land as many conversions as possible. This implies you have to make exactly the right trade-offs. However, today, the customer uses a variety of devices to engage themselves with brands on multiple channels. Thus, it becomes hard for you to predict your target user’s behavior.
Predictive modeling uses artificial intelligence and machine learning framework that enables you to predict what’s most likely to happen based on the desired scenarios. By forecasting the future viewing habits of your target audience in the form of visualizations on the dashboard helps to increase conversions in your set budget or you can even lower your budget while maintaining your current conversion rate.
2. Effectively Detect Anomalies (Before they happen!)
“You have to take risks. We will only understand the miracle of life fully when we allow the unexpected to happen.”~ Paulo Coelho
Unexpected action is inevitable to occur in your data and it can be both good and bad. Good, implying that your campaign is performing much better than you expected and bad, implying that something wrong has happened—a bug that’s causing the problem, a tagging error, even corporate espionage. No matter, what’s the cause of the anomaly, it is always considered good to identify the one and to get a long-term vision of your campaigns and where anomalies occur over time.
Traditionally, it took a lot of time and resources, assuming you weren’t too busy simply cleansing data and preparing reports.
However, now you have a miracle in the form of predictive modeling. It can automatically detect statistically significant data anomalies during specified periods and can visualize unexpected traffic spikes or dips that can occur in the near future with clear visualizations on the dashboard.
How Epson uses Predictive Modeling in Dashboards to Detect Anomalies
Real-time dashboards are not the only way that Epson is raising visibility into issues. With predictive modeling integrated into the dashboard, powered by Adobe Sensei, they are finding ways to uncover unexpected website behaviors based on actions, errors, and conversion.
“Website errors can be hard to track down and even harder to replicate. What Anomaly Detection does is help us pinpoint where and when issues are occurring, so that we can get in front of errors and minimize the impact on conversion or leads.”~ Scott Sturcke, Director, Online Marketing Management at Epson America
3. Minimizing Customer Churn
“Get closer than ever to your customers. So close that you tell them what they need well before they realize it themselves.” ~ Steve Jobs
Churn rate in its broadest sense is a measure of the number of individuals or items moving out of a collective group over a specific period. Churn rates are as high as 30% per year in some global markets, thus, identifying the ways to retain at-risk customers becomes a top priority for business leaders.
Predictive modeling in dashboards can help marketers to combat this high cost of churn rates. It can help to analyze why customers churn and which customers are most likely to churn going forward. Thereby, helping you to predict and target the customer base that may be thinking of migrating to another provider.
Data is becoming a vital asset to the function of marketing. However, figuring out whether your data analysis on dashboards is providing you the answers to the following questions is not an easy task: :
- Will your high-value audiences continue to engage?
- Can we identify where they may drop off?
If the answer to the above questions is NO, then you are indeed not on the right track of marketing. The true value of decision-making is realized when you integrate your marketing dashboard with predictive modeling to find answers to the queries that can impact your business in a big way.
Remember, seeing the future isn’t a superhero power. It’s just a marketing tool in the form of a dashboard integrated with predictive modeling.