Editor's introduction: Maybe everyone's daily work involves more or less business analysis modules, so when the society generally pursues efficiency, can we use tools bulk sms service to achieve business in our daily business? Maximize analytical value? Perhaps, Amazon SageMaker Canvas launched by Amazon Cloud Technology is one of these types of tools. The author of this article has conducted an evaluation experience on it, let's take a look. 1. The truth is that we are all doing business analysis Whether you realize it or not, we actually do business analysis every day. Try to imagine these scenarios: If mobile game operators want to increase the proportion of paying users, they will analyze the user behavior to find out the factors that affect the payment, so as to adopt targeted operation methods. When the supermarket bulk sms service owner purchases goods, he will comprehensively consider factors such as previous sales, location, season, etc., and analyze the amount of inventory to be prepared for each item.
When managing clients, the real estate agency will follow up according to the client's personal situation, background information and intention information, so bulk sms service as to increase the transaction volume. Although the protagonists of the above scenarios are not professional business analysts, they know how to make smarter judgments. And this is precisely the essence of business analytics: by collecting and processing business data, analyzing a trend, pattern or root cause, and making data-driven business decisions based on these insights . Second, the problem is... Although we are more or less in our own way, through "business analysis" to complete the work, but the problems are also emerging one by one. 1. Expect to go further A large amount of data, many influencing factors, lack of professional modeling capabilities, etc., will make us often stay on the surface when actually analyzing the bulk sms service business, and miss the deeper insights behind it. For example, when analyzing the factors that affect user payment, our operation classmates locate a variety of related behavior indicators: User source: users from channel
A pay a higher proportion; Average daily active time: Active users pay a higher proportion; Average number of daily interactions: users with more interactions pay a bulk sms service higher proportion; Whether to participate in incentive activities: The proportion of users who have participated is higher. Although the above conclusions can help us determine which characteristics of users are more willing to pay, we would like to know further: which indicators have a greater impact, whether the indicators will affect each other, and whether the final effect can be predicted before the next operation. Often there is no way to start. 2. Is the conclusion correct? Can you quickly verify Perhaps with business experience, we can perceive that a certain indicator is a key factor in determining user payment, or can predict sales in the next bulk sms service quarter. But the question is: whether we can quickly verify our conclusions with data; or whether there is a more professional way to prove our conjectures. 3. The cost of communication In addition,