Website Analysis Hacks Optimization online payment process

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This article extracts from the website Analysis master Eric T.peterson "web site measurement Hacks"

–hack#83 "Measure the Checkout Process"

Compared with other links of the site analysis and optimization, online payment process analysis and optimization of the benefits of a lot more.

For online retail e-commerce sites, the payment process is the most important in every link that needs to be optimized. Fortunately, it is easy to analyze, and it is also possible to optimize it through detailed analysis. Following this simple step, starting from day one, you will be able to recognize changes in some of the optimization measures that will allow retailers to add to their investment.

Step one: Establish a baseline

The first step is to establish an analytical baseline that periodically effectively monitors the payment process. There are two basic metrics to track trends, and they provide a good baseline for analysis:

The rate at which payments are completed within one visit (for example, a fiscal month) during the same access analysis period:

Include payment complete Thank you page number of visits/include the number of visits to the first page in the payment process

Ratio of payments made across the access analysis period (the average time period during which the shopper completes the purchase of the item):

Arrival Payment Completion Thank you page number of visitors/arrival of the first page in the payment process

In the payment flow funnel analysis, you should understand each step in depth and see what happens in each step. You should be aware of the following metrics in each step of the payment process:

Number of steps reached: number of visits to each step

Potential sales: Total potential sales per step (based on the number of items left in the cart and the number of items abandoned in the cart)

To the next step: number of visits to the next purchase step

Completion rate: The percentage of visits that are usually expressed as a percentage of the continued purchase of the item, or that are still in progress

Leave the funnel rate: the percentage of access to the site that leaves the payment process but still accesses it.

Departure rate: The percentage of visitors leaving the payment process and leaving the site at the same time.

Potential loss: Sales from the checkout process.

It is to be remembered that monitoring the payment process is only a special case of "monitoring multi-step processes". Web Analytics reports typically list each step in the payment process and the corresponding metric value in a report. (Refer to the table below)

Payment Flow Funnel Analysis report

For each of these steps, you can learn about customers buying goods, or not paying, or even leaving the site directly. In addition, the financial implications of losing these customers are also at a glance. After reading the Web Analytics report above, you'll probably say, "This is a very good report, but how can I prevent a lot of customers from losing out on the payment process?"

Step Two: Diagnose the problem

The next thing you need to diagnose is what is causing the loss described above. The key to diagnostic analysis is to find out where users are stopping and where to go. In most cases, you can make assumptions about the root causes of these actions.

The final data of the diagnostic payment process is to click the stream data and to show the exact path of the user in each step of the process through the analysis of the click Stream data. It is useful to divide these actions into the following situations:

Exit directly from the site

Advance to a subsequent step in the process. If the step does not have more than one optional next step, it will only go to the following step.

Go back to a previous step

We recommend that you make a page path map with metrics and cover each step of the payment process. Although you may already know the big problem points, you should now be more specific about what caused the loss and whether it was the opposite or the behavior outside the process that caused the problem. Next question you might ask, "What's the worst?"

Most Web analytics tool providers can provide a number of path analysis reports (refer to the following figure) to provide you with the visual data for a comprehensive diagnostic payment process. These reports are the modifications to the information presented in the previous Payment Process Funnel Analysis report, to highlight a problem with a page in the payment process, in this case, you can find out whether the user enters "payment step two" after entering "payment step one: Log in";

Page Click Flow Report based on single session (access)

Similar reports and visual information can help you better diagnose the problems highlighted in the table above. You will be amazed at the value of this ability to visualize information, for example, in the Payment Process path Analysis report above, you can find:

Did not jump as expected. For example, after a user enters the payment link, 9.2% of the users return to the "View Cart" page, and there are 162 visits to the homepage.

The part where the error occurred. For example, jump to the password error page 4,436 times, to the Forgotten Password page 979 times.

Summary

Overall, the way to monitor and optimize the payment process is straightforward:

1, the establishment of a good measuring benchmark after monitoring the trend of large.

2, monitor the user's behavior in each step of the process to find the key point of the problem.

3. Dig deeper and determine how much they will go if the customer does not move forward and imagine why they are behaving.

4, most of the occasions, to provide a more in-depth analysis of the behavior of specific user groups, but also to ensure that any of their actions on the interests of another group impact changes, the analysis of each group of customers is more meaningful. Typical groupings include new visitors and visitors in contrast, most of the most valuable customers, customers entering through marketing campaigns, customers who can generate high levels of classification, and so on.

5, at the same time using the conversion rate and transaction amount, access to the established path to the sales of customers.

6, according to the effect of return on investment, to optimize the site's expenditure list priority.

7, try to do everything to make up for the site's vulnerabilities.

8. Measure the impact of these changes and continue to repeat these steps.

Finally, if you have mastered the continuous optimization process, you should soon be able to make subtle but important optimizations in the payment process.

-Brett hurt and Eric T. Peterson

(Copyright GUI Lin website Analysis blog All, welcome to reprint, but reprint please specify the source.) )

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