How should products and operations use big data for conversion analysis?

In the many marketing copy screen-sweeping incidents in 2017, product and operation personnel have increasingly realized that traffic ≠ conversion . Conversion rate is the most core and critical data for measuring a product and an activity. Therefore, conversion rate is the core of whether a website can ultimately make a profit. Improving the website's conversion rate and increasing sales are the key.

Today, let’s talk about how to do conversion analysis through big data from the perspective of product and operation?

First of all, we need to be clear about what conversion rate is? What data directly affects it? What are the factors that influence these data?

Conversion rate refers to the ratio of the number of completed conversion behaviors to the total number of clicks on promotional information within a statistical period. Simply put, this is the formula:

Taking shopping on e-commerce platforms as an example, when the total traffic is constant, the more people buy, the higher the conversion rate.

A successful purchase behavior of a user involves multiple steps, such as search (exposure), browsing, adding to shopping cart, checkout, and payment. If there is an error in any step, the user may give up the purchase immediately. According to relevant data, the conversion rate of most e-commerce companies is only around 0.5%, which means that 99.5% of the traffic is wasted. (It hurts to hear that)

So, how can we increase the number of buyers? How can products and operations be used to increase product sales?

1 Basic analysis: Direct influencers of conversion need design

The basic stage of conversion analysis mainly involves the analysis of conversion steps and the monitoring of conversion rate trends.

As we all know, traffic is in the shape of a funnel, and turning traffic into consumers involves about five steps. These 5 steps are enough to filter out 99.5% of potential users . In addition, according to statistics, among several larger B2C websites, traffic data is increasing, but the time customers stay on the website is decreasing. In the era known as the eyeball economy, each Internet user stays on an e-commerce website for about 17 minutes .

What data should website operations and product personnel know during this analysis phase?

During this stage, the data that the website platform can directly obtain is large and complex. After collecting the data, the operators classify and organize the data, which are generally divided into the following categories: demographic attributes, social attributes, behavioral habits, interest preferences and other aspects.

Demographic attributes, including age, gender, height, region, education level, income and education

Social attributes, including social position, marital status, housing and vehicle, social relationships, etc.

Behavioral habits, including preferences for sports, leisure travel, hotel accommodation, diet and daily life

Interests and preferences, including shopping, games , sports, culture, etc.

The collection and analysis at this stage provides the base for user portraits . Provide certain data support for later operation plans , copywriting planning, channel planning, etc.

2. Intermediate analysis: Analyze conversion from different dimensions

In the past, people believed that data was a resource for the enterprise. In fact, data is an asset that can create value for sales . In order to better improve the conversion rate, it is necessary to consider factors in different dimensions, which is also a segmentation of the data from the previous stage. For example: access source, operating platform, jump page, operating system, browser type, etc.

At this stage, we first need to understand which customers are browsing the website and which ones are definitely here to buy something, which ones are just browsing, and from which entrance they enter;

Secondly, how many product pages did users who did not purchase view, how many put things in the shopping cart but did not pay, and how many did not view a single product page;

Third, how many customers made purchases.

Fourth, it is very important to know that after customers log in to the homepage of the website, in addition to the 40% pop-up rate, the remaining 60% of users enter the product page through which channels, and what is the proportion of payment after entering through these channels.

Finally, how many people have added the product to their carts, and is there a possibility of a recall?

Only by segmenting and organizing the huge database of the website platform can we discover the hidden user behavior logic behind it, so that product personnel can optimize from the product perspective, while operations personnel are responsible for optimizing activities, special topics, product details pages, etc.

For example, for a user I worked with before, the background data showed that many people added a certain product to the shopping cart, but none of them paid for it. In order to recall these customers, the website immediately pushed a coupon, and finally recalled 30% of the orders.

3. High-level analysis: multi-dimensional cross-analysis, continuous optimization and iteration of products

Products in the Internet industry all have a consensus: take small steps, run fast, and iterate quickly . Only in this way can we create products that are loved by users.

Through the data collection and analysis in the last two paragraphs, the website staff already has an idea of ​​the website's strengths and problems. At this stage, you need to calm down and analyze and correct from specific dimensions and points. At this stage, it can be said that data drives product and operational decisions.

For example,

Which advertising channel has better traffic? What kind of brand content is more easily spread by consumers?

How to organize and arrange web page content to better meet the personalized needs of visitors;

How can old customers return to the website and purchase products repeatedly?

How to reduce the number of orders with failed payments?

The author of this article @ 99click compiled and published by (Qinggua Media), please indicate the author information and source when reprinting!

Product promotion services: APP promotion services Advertising platform Longyou Century