This question cannot be answered with a one-size-fits-all setting.The decision-making cycle of foreign trade B2B is long. First of all, we must determine whether the data is poor because no one has looked at it, because they are not interested, or because they are interested but have not entered the sales process.The most questionable thing at present is that stacking too many interests and positions will make the audience too narrow or the logic unclear, making it difficult for the system to stably explore.
It is recommended to conduct a reverse check first: work backwards from the final quotation opportunity you want to obtain, and determine what content the customer needs to see, what evidence to obtain, where to click, and what information to submit.The advertising system will look for people who are more likely to complete the action around the selected goals and optimization events. Wrong target selection will result in a large amount of cheap but no commercial value data.If these steps are not connected, optimizing for reach, clicks, or fans alone will be difficult to produce stable results.
The first action in this question is: first establish a layer with industry or application interests, then narrow it down as necessary with procurement, engineering or management-related signals, and retain a wider test group.Then check them one by one by "working backwards from business results to conversion positions and optimization events, and then designing concise campaign and ad group structures based on countries, customer types, industries and data bases."Don’t change positioning, materials, audiences, and hosting pages on the same day; if you change too many variables at once, you won’t be able to replicate the results even if they get better.
Two sets of data are used when measuring: the platform side looks at target event cost, effective lead rate, country and customer matching, frequency, learning status and sales acceptance rate; the sales side looks at company matching, demand authenticity, quotation possibility and follow-up results.In particular, it is necessary to compare audience size, delivery stability and lead company matching to prevent the operations team from only reporting good-looking superficial data.
A practical judgment is: if the data is small but the customers are accurate, it can continue to be accumulated; if there is a lot of data but the customers are wrong, the screening and expression should be corrected immediately.It takes a week to observe execution issues, a month to judge trends, and then a complete procurement cycle to test whether the target audience is actually creating business opportunities.
