Twitter’s precise user screening, don’t just look at the number of followers, really look for people who are related to the product

DoWhen Twitter acquires overseas customers, the most common situation is that the account looks busy, but there are not many customers that can actually be handed over to sales. There are a lot of followers, likes, and comments in the comment area, but these users may include peers, ordinary onlookers, content enthusiasts, or some may just pay attention temporarily because of a certain popular content. The real solution of Twitter's precise user screening is not to load all interactive users into the customer database, but to determine as quickly as possible who is related to the product and which is just ordinary traffic.

Instead of pursuing more users first, do a simple match with existing leads. Whether the country is right, whether the industry is compatible, whether you have read the product content, whether you have actively entered the website, and whether you have submitted inquiries. The clearer these conditions are, the more valuable the list you get from sales will be.

Don’t screen users first, set your own customer standards first

If you don’t even think about who your target customers are,No matter how many Twitter users there are, it is difficult to screen accurately.

For example, in cross-border logistics, the really relevant people may be cross-border sellers, independent merchants, and supply chain leaders.

When working on enterprise software, you may pay more attention to company leaders, operations, sales management or marketing personnel.

For industrial products, you may focus on procurement, engineering, dealers and factory-related groups.

So the first step is not to askWho has more fans on Twitter, but first determine a few basic conditions:

target country;

Target industries;

Suitable customer types;

What problems are mainly solved;

What kind of people were easiest to consult in the past.

Once these conditions are clear, subsequent screening will be much easier.

If the country is wrong, no matter how much interaction you have, it may not be worth the sales follow-up.

Assume that the product is currently only for the US market.

If a user from a non-target market likes every day, even if the interaction is very good, it may not be suitable for direct sales.

On the other hand, although a local user in the United States has only interacted two or three times, but his work direction is highly related to the product, and he has actively entered the official website to read the quotation, this kind of clue deserves priority processing.

soWhen filtering accurately on Twitter, you can start with the simplest market conditions.

Country matching, continue reading below.

The country is obviously not within the current business scope, so we will first put it among ordinary content users.

This will reduce a lot of invalid judgments in the first round.

The second step is to see if this person has anything to do with the product.

After the country meets the requirements, we will look at the business relevance.

What content does this person usually post?

What industries are you focusing on?

What career or company direction is included in your personal introduction?

Is the interactive content directly related to the company's products?

For example, when selling marketing software, users often discuss advertising, sales,CRM, customer development, this kind of business is obviously highly relevant.

If a user mainly posts sports, entertainment, and game content and only occasionally likes a corporate account, there is no need to directly treat him as a precise customer because of one interaction.

The key to Twitter’s accurate user screening is actually to continuously exclude weakly relevant groups.

The third step is to see if the user has followed the"Look at content" to "look at products"

If a user is related to an industry, it cannot directly indicate that he or she has purchasing needs.

What really deserves continued attention is whether there are any further moves.

For example:

Check product-related content repeatedly;

Take the initiative to ask about features or prices;

Click on the corporate homepage link;

Enter the official website or landing page;

Download information;

Request a demo;

Submit the inquiry form.

These actions are closer to business than simple likes.

Especially those who have actively entered the official website or submitted a form have transformed from content users into real sales leads.

At this time, it is more natural for sales to intervene.

can putTwitter users are directly divided into three categories: A, B, and C.

There is no need to make a very complicated scoring system, a simple three-layer system is enough.

Type A users are highly related to the business and have already taken active actions such as consultation, forms, and trial applications.

This category should be given priority to sales.

Category B users have relatively matched countries, industries and products, and have interacted with them many times, but have not yet made clear inquiries.

This category can continue to be cultivated through content, cases, and product information.

Type C users only have ordinary likes, follows or weakly related interactions.

This kind of people don’t need to rush to reach sales, they can just continue to serve as content audiences.

After dividing it like this,A Twitter account may still have tens of thousands of followers, but only a small number actually make it onto the sales list.

This is normal.

Twitter’s accurate screening is most afraid of treating the number of fans as customers

100,000 fans does not equal 100,000 customers.

5,000 commenting users does not equal 5,000 sales leads.

The real number of customers depends on how many people have completed the transition from content to business.

For example, one month:

100,000 people saw the content;

5,000 people interacted;

800 people entered the website;

200 people submitted the form;

in80 people meet the target market and business conditions.

In the end, it may be this that is worthy of sales focus and follow-up.80 people.

front100,000 traffics are still valuable, but they mainly belong to content and brand communication, and should not be stuffed into the sales system.

By clearly distinguishing people at different stages, the data will not become more chaotic.

After the user leaves their contact information, they then enter the number screening process.

whenTwitter users have taken the initiative to leave their mobile phone numbers through normal entrances such as the official website, forms, event registrations, etc., and then enter the contact information later.

At this time, Digital Planet can take over.

For example, a batchOverseas customers brought by Twitter have already left their numbers. They can first sort out the international number format and remove duplicates, and then use Digital Planet to filter the status of WhatsApp, Telegram, LINE and other platforms based on subsequent communication needs.

It turns out there are only:

USA

Twitter source

consultA product

Phone number

After sorting, you can add:

WhatsApp has been activated

Telegram related status

target communication channel

After getting the sales, there is no need to try each platform again.

But it must be clearly distinguished here. Digital Planet solves existing contact information and social platform status, and cannotOrdinary Twitter fans directly become customer data of mobile phone numbers.

The previous target group judgment still depends on content, interaction and business information actively left by users.

Why Type A Customers Are Worth Following Right Now

Category A customers usually have relatively clear business signals.

For example, I just asked about the price;

Just applied for product demo;

Just submitted the purchase request;

Just filled in the company contact information;

Or enter the official website for consultation after viewing the product content many times.

If such users delay contacting us for a few days, they may have already gone to another supplier.

So after the sales list comes out,Type A users are best ranked first.

And there’s no need to ask about the first sentence"Are you interested in our products?"

Now that we know where he came fromIf the Twitter content or product page comes in, just continue the conversation directly from that question.

Communication will become much more natural this way.

Type B users should not rush to push

Although type B users are matched with the product, they have not yet made any obvious purchasing actions.

This may not be the right time to send a quote right away.

You can continue to use industry content, cases, product comparisons, frequently asked questions, etc. to cultivate.

For example, if the user has been paying attention to a certain function, continue to show him the application scenarios of this function.

If you are concerned about a certain type of solution for a long time, you can slowly be directed to the official website information or trial entrance.

After he actually enters the form, consultation or product page, upgrade toCategory A.

Selling this way will not take away allTwitter users all handle it the same way.

Accurate user screening also depends on the final sales results.

Filtering rules cannot change forever.

After doing it for a while, what can you look back on?Twitter users really produce results.

Leads from which countries are more likely to be sold;

In which industries users responded more positively;

Which content brings higher quality forms;

Those who seem to interact a lot rarely enter the inquiry;

Which users have the shortest path from attention to transaction.

These data will slowly tell you what your real target customers look like.

In the next round of screening, these features can be placed higher.

This is more valuable than increasing the number of followers all the time.

Twitter’s precise user screening ultimately leaves sales time to more suitable people.

What's really lacking on Twitter is usually not users, but standards of judgment.

First look at the country, then look at the industry and business relevance, and then look at whether you have entered the product page, submitted a form or actively consulted. After you actually leave your contact information, you can sort the numbers and filter the target platforms through Digital Planet.

Finally, users are divided into three categories: priority sales, continuous cultivation and general content audiences.

Twitter's precise user screening is not to find more numbers from 100,000 people, but to determine who is really related to the product as quickly as possible. The list can be shorter, but it should be more worth talking to the person in sales.

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