Everything and anything regarding propensity to buy model.
What is Propensity to Buy?
By definition, it is the likelihood of a potential customer to purchase something, a.k.a Purchase Propensity. It is applicable to almost any sort of business, however, it's especially applicable to the e-commerce industry.
E-commerces experience very regular website traffic and every single visitor is a potential customer. In reality, not everyone ends up purchasing something. However, they all have one thing in common. They all have some website visit behavior and some likelihood in terms of the probability to purchase something.
A Propensity to Buy Model predicts which of these visitors (potential customers) are going to purchase something and which are not. Now that we know what this model does let's try to understand why it is an important factor in e-commerce or other types of businesses.
What Makes it Important?
E-commerce websites attract a huge amount of traffic. Ever wonder how many actually end up buying something? On average 2% of the visitors actually buy something. These visitors have certain behaviors that distinguish the ones that buy something and the ones that don't. These visitors can be modeled using their website visit behavior to predict their likelihood to purchase something. This has two hidden benefits:
- The company can differentiate visitors that are highly likely to buy something along with their behaviors.
- They can target these highly likely visitors to take immediate marketing actions like; campaigns, coupons promotions, etc.
Reaching out to the right visitors who are higher likely to purchase will secure the potential sales and eventually in long run increase the revenue.
How to Predict Propensity to Buy?
There are of course more than one way to achieve this on many different platforms. Some are simpler than others and some are more accurate than others. Today I aim to show the simplest and the most optimized way to achieve this.
The other thing you need is the Store/Website Visit Data, Sales Data, and Product Data. If you don't know how and where to collect these data from, Enhencer got you covered whether you have a Shopify store, Woo-Commerce Store, or any other e-commerce store. Enhencer has a custom-designed API that takes care of all of these. Once you connect your store/website using the API, Enhencer starts to collect all these data automatically.
What if I tell you that’s all you have to do to obtain all the predictions, It’s crazy right?
Well as crazy and unbelievable it sounds like, that’s actually all the user has to do. After connecting/uploading the data to the platform Enhencer does something that no other platform does.
- On normal occasions, the raw data should go through some Feature Engineering, whereas Enhencer does that Feature Engineering automatically on the data.
- When it’s time to train some predictive model, Enhencer does that for you too. Enhencer Trains a lot of Machine Learning Models on the data and chooses the most accurate one automatically.
The Predictions and The Results
Afterward, Enhencer presents the predictions and predictive analytics on a dashboard like this.
Without giving too many details I will try to explain what is the takeaway from this dashboard. However, If you want to read the more detailed version then just click here: https://enhencer.com/help-center/purchase-propensity
Segmentation: Enhencer segments all the visitors based on their past website visiting behavior and past purchase behaviors. The top segment contains the visitors who have the highest probability to purchase and the purchase probability decreases as you go down the segment list.
Segment Insights: What's more, is Enhencer also provides the behaviors of the visitors for each segment as well. At this stage, you not only know which visitors are most likely to purchase but you also know what sort of website visit behavior these visitors have.
This is a very powerful insight as this shows what kind of behavior leads to a purchase and thus this segment can be targeted to maximize the purchase propensity from these kinds of visitors. This brings out target groups for future marketing campaigns/actions.
The Implementation: Enhencer makes it super easy to implement these results. One can use the custom-designed APIs to integrate with their own e-commerce website/store and obtain live predictions on the visitors. On the other hand, users can download these results and predictions in excel formats as well.
Behind the Curtain
These all might sound too good to be true but it's all true and it's all here for everyone to take benefit of. however, Enhencer uses machine learning algorithms as its backbone. That's one of the reasons behind these auto feature engineering and auto model training.
This does not mean users can not manually do things even if they wanted to. By default Enhencer does all these automatically. Users can take matters into their own hands at any time and at any stage of these processes. All these are to make predictive analytics much easier to conduct. This makes creating a propensity to buy a model and predicting purchase likelihood super accessible to everyone. Users don't have to write any codes and everything can be accessed using the super-intuitive user interface.
This also saves a lot of time for everyone. For such a project, a traditional approach would have taken days or even weeks of time whereas using Enhencer this will only take a few minutes.