One of the things that I love about marketing is, we often refer ourselves as both magicians at the same time a psychologist, a magician, we create an amazing idea and put that into tangible things in order to serve as a purpose, on the other hands, we need to have the accurate sense to understand the audience when we speak out our products/services, so we will be able to predict, target the potentials and in the end to convert, that’s basically how the marketing funnels work. But are they any scientific way to predict your audience behaviors before launching your tactics? Let’s find out today!
According to SAS, they define predictive analytic as follows: Predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to provide the best assessment of what will happen in the future.
You might find this explanation as bored as what the textbook says, however, they simply just want to convey you that:
The purpose of predictive analytics is to use data to predict what will happen in the future. – By MTL marketing ninja
Bingo! That’s it, it is actually not hard to understand, as long as you have the historical data through your sales or spreadsheets, we will be able to crunch some numbers in order to sound viable decision for the future, for simplify the process, let’s do not talk about all the complicated machine learning, AI regression yet, for small or medium companies, what they basically need are always making sure that 1) Understand your demand 2) Fill the gap of the supply, and the bottom line will be always DO NOT FU*KED UP YOUR RESOURCES PLANNING OR CASHFLOWS on earlier stages.
Adopt predictive customer behavior models into your strategies
One of the reasons why company like Amazon can dominate the world, they are probably the top elite on predictive data-driven technologies in order to understand its customers better than anybody else. Every time when you are shopping on the site, your search queries are going to be recorded and analyzed through machine learning and that’s why in the end amazon will respond you with appropriate product categories or even promotion catalogs, in other words, they are basically hypnotizing you with all the implicit messages at their back end so you will not be able to resist but BUY BUY BUY, this is one of the predictive analytic strategies that have been commonly used on most E-commerce platforms.
Three of the predictive strategies involved as follow by using an algorithm such as regression, which is basically a sequencing study of some variables on particular behaviors such as like buying a specific product during the specific season..etc, the common three predictive analysis models mostly involve in the following criteria:
Recommendation models:
It’s very common to see the site that you shopped often recommend you similar products, services or even ads such as promotion with the items that you actually shopped before but offering you an even bigger discount! Another example will be the item that you used to shop but it appeared on other sites such as your inbox or news sites..etc, we also called this practice re-marketing. Overall, the recommendation models including all the up-sell, cross-sell or even next sell methods, the predictive analytic strategy often occurs when you are doing a sequence of actions on the websites such as clicking a certain category, checking specific items, keyword or even the loading duration.
Make sure you don’t panic when you receive promo in your inbox from companies like Netflix, Spotify or Amazon. They are basically just doing what they good at, the key-point for this predictive strategy is, each visitor will have their own prediction with appreciative suggestions.
Audience cluster segment Model
This might sound difficult to understand, but think about the term “cluster”, it simply means grouping similar variables together, pretty much resembles what we so-called “stereotype” in with certain races or population, people often use information such as demographics, interests, age, niche or even genders info to predict what people are going to do next as a group level.
An example will be the male / female behaviors, so in term of predictive analysis strategy, Marketing professionals usually use “what color that man preferred?” or “what product that woman would love to search?” or even “what kind of tools that musician usually buy?”, this is what I refer to the cluster segment, you might see lots of specific theme landing pages, such as a landing page that create for musician or home theater renovation contractors, they often have similar needs under each category, if you want to go more profound, you even mix the cluster segment + the recommendation strategies that I mentioned above, here are the success cases that I had tried before.
1) Use specific landing to acquire similar interests (e.g musician) to suggest them audio cables
2) Create a Black Friday / Cyber Monday landing page and push them DEALS PROMO
3 )Target female audience by creating a “feminine color theme” landing and push them items
Of course, you can use whatever creativity that you want as long as you can predict it accurately.
Direct Prediction models
Every time we are calculating how much clicks that we will get through our budget planning, our stock forecasting as well as conversion rate between seasons or un-subscription rate, we are all under this prediction models. This is the most direct because it does not fluctuate that much, for example traveling agencies like Sunwing might deliver Cuba trip for 7 days especially around June / July for only $700, or when cloth company Simon is introducing the Spring wear on the month of Feb…etc. Those are the direct prediction and it does not change that much every year.
Here are the conclusive GOLDEN Rules for conducting predictive marketing strategies:
-Select appropriate predictive models that match your current tactics-Targeting the right customer at the right time with the right contents-If you can go AI or automation, just do it! (send requesting reviews, discount notice..etc)-Your predictive analysis campaign needs to optimize from time to time-You need to have a sense of purpose about the campaign before predicting your audience’s behavior.
I guess that’s enough content for me today and now I am heading to bed, hopefully, this article will be useful to you, feel free to let me know what you think at the comment and feel free to share this article for me on social media if you can so I can get a chance to reach an even bigger audience.