Georgetown Geo Battle: Ranking up without consulting, where is the customer?

Our company recently purchased CRM and conducted research in bean bags throughout the process, taking a customer through the entire path from search to contract signing.

1. Customers use AI to find suppliers, taking a four-step link

No one takes a look at AI rankings to sign a contract.

You may want to ask: What does it have to do with me if you buy a CRM?

This is not a CRM-only path. No matter what you sell, as long as your customers will search and compete on AI before buying, they will go the same way. We use CRM as a sample to take apart what customers are doing at each step, what AI is searching for, and which brands will be brushed off at which step. You can read and compare your business.

In four steps, each step is brushing people:

The cognitive layer allows the customer to see you. Layers of contrast and detail let the client choose you. The validation layer allows the customer to find you. The action level decides whether he will buy it after buying it, and whether to recommend it or not.

Where there is no content, the customer is stuck on that layer.

II. Cognitive layer: search for "which company is good", AI recall ranking and horizontal comparison

The goal of the cognitive layer is one: to squeeze into the shortlist.

A "which home is good", the AI broke down 4 words

What we searched for was: "Recommend a few companies that are more reliable in doing CRM systems in China".

The AI decomposed itself into 4 search terms and turned over 23 pieces of data:

1. "Recommended by domestic manufacturers of reliable CRM systems"
2. "CRM Vendor Classification Large Enterprises Small and Medium Enterprises Domestic CRM"
3. "Domestic mainstream CRM brand comparison Vendor A Vendor B Vendor C Vendor D Vendor E"
4. "Introduction of domestic CRM system manufacturers"

Three laws.

The AI will make up for the dimension itself.In the second word, "large enterprise/small and medium enterprise/localization", the user did not say it at all. But purchasing CRM will definitely be better than enterprise scale adaptation, more than Xinchuang requirements, AI for you to think of.

AI will compete on its own.The third word brings up 5 brand names directly. If your brand does not appear in such horizontal contrast articles, the AI will not even take you with it.

Words like "recommended" and "vendor introduction" are used almost every time.The title is written in the company name, without the scene words and the selection dimension, the AI can't turn over to you.

AI does not rank in the overall list, classified by location, it is more detailed than who

The title of the AI's response reads: "Recommended by domestic reliable CRM vendors (classified by location, no ranking)".

Categorize first. The first category is called "enterprise-level PaaS CRM", and three are recommended. Each family writes that you can directly judge whether it is suitable for you or not:

Vendor A (head PaaS type).Domestic head CRM has been selected into the international industry analysis report for many years. It has strong PaaS capabilities and mature AI sales forecast, lead score, and BI analysis. It supports public cloud, private cloud, hybrid cloud, and Xinchuang adaptation. It is suitable for large and long-cycle B2B sales such as equipment manufacturing, IT, and industrial equipment, and is a group-type enterprise.

Vendor B (connected).Mainly connected CRM, native docking mainstream office collaboration platform, mature channel distribution and FMCG solutions, marketing - sales - after-sales integration. Suitable for medium and large B2B, fast consumer, agriculture and animal husbandry, channel dealer management.

Manufacturer C (old domestic).Veteran domestic PaaS CRM, highly customized modeling, mature privatization deployment, and many financial, medical, and energy cases. Suitable for large and medium-sized groups that are highly compliant, highly personalized, and want to be privatized.

AI puts who in front, regardless of whose name appears more often, to see whose data is detailed, objective, and systematic.

The whole article is full of advantages and no disadvantages. Read it like an advertisement, and the AI will suppress it. Only a bare brand name, can't even enter the list.

How the cognitive layer prepares content: horizontal comparison pulls at least 5 brands and matches the comparison table; each company's advantages and disadvantages, establishment time, deployment mode, core capabilities, and suitable for the industry are all written; multiple third-party platforms, don't just stack them on their own official websites.

III. Comparison layer and detail layer: search for "how much money/how", AI recall price and reputation

This layer is the easiest to leak and the easiest to be picked up by the opponent. Clients call you by name, but they can't find your stuff.

Search three prices by name, and the AI flipped 25 articles

The cognitive layer screened out three companies, and then searched: "How much is the crm system of Vendor A, Vendor B, and Vendor C respectively".

AI opened 5 words and turned 25 articles:

1. "Vendor A CRM Fee Standard Version Account Price"
2. "Vendor A Vendor B Vendor C CRM Price 2026"
3. "Vendor B CRM price subscription fee"
4. "Vendor C CRM quote public cloud privatization"
5. "Vendor A Vendor B Vendor C Privatization Deployment Fee"

The customer's abacus is all spread out: how bad is each version, public cloud or privatization, the latest price in 2026. "2026" is actively added by AI, it is looking for new content.

In 25 articles, Vendor A did not have any of its own content

The sources of AI use are: the charge page of Vendor B's official website, the recommendation page of Vendor C's official website, the 2026 measured quotation of another CRM vendor, and the summary of 9 domestic prices in the technical community.

Only Vendor A does not have its own official website or price page.

Customers come to check your price, and the result is an all-rival website and third-party evaluation. If you don't speak, the AI will answer for you with someone else's content. Customers can't find your official offer, so they naturally go to the one with more information.

AI spelled out the price, there are zero integers

AI also added: all three are basic subscription fees plus implementation fees plus value-added module fees; privatization has no public price, and should be discussed separately; implementation fees start from tens of thousands per person per day, and privatization is hundreds of thousands to millions.

AI only grabs sentences with numbers.You write "good value for money" "flexible price", it does not quote a word. You write "Professional version 78 yuan/person/month, purchased from 2 years", it is copied directly.

Lock one down to dig, the AI even lists the slot points for you

After the price comparison, lock the manufacturer A search: "How long has this company been established, how is the word of mouth?".

AI broke down 2 words and turned over 12 articles. Answers are divided into three sections: company information, positive reviews, and slot points, and are displayed side by side.

Four points of praise: strong B2B long-term sales capability, mature PaaS platform, mature AI prediction and BI analysis, and many large customer cases.

The slots are written more specifically than positive reviews:

• The cost is high, the implementation fee is large, and it is common for complex projects to cost more than 100,000. Contracts are usually signed from 2 years onwards.
• Getting started is complicated, there are many functions and configurations, and front-line sales are hard to learn
• Implementing delivery is the biggest variable. It depends on the consultant's experience. If the consultant does not work, the system will become a record tool.
• Small and medium-sized teams use poor price/performance ratio, "kill chickens with cattle knives"

The customer stares at a brand to drill down, not only to know where you are, but also to know where you are. It is not possible to have a price alone without a review, and it is not possible to have all positive reviews without any shortcomings. AI dares to quote the content that coexists with the advantages and disadvantages, because it reads like a real person, not like an advertisement.

This layer is selected, one of the four things is indispensable

1. Write the specific number of the price, do not write "cost-effective".
2. One article only tells one version or one function, don't block all services in one article.
3. Putting real evaluations and cases, customers most want to know how people in the same industry use them.
4. The advantages and disadvantages are written together, and the content AI on both sides is more dare to quote.

4. Authentication layer: search for "where/how to contact", AI recall address and phone

The most people have fallen from this floor. The front is better, a reservation entrance that can not be found, the customer will be replaced on the spot.

Find the contact information, the AI gave two different addresses

After checking the price reputation, lock the manufacturer A, search its website, company address, and contact information.

The AI broke down two words and turned over 10 articles, and the results given had obvious problems: the official website had links, but the address listed two - one from the industrial and commercial registration information, one from the official website, and the difference between the two places was more than ten kilometers; the branch only listed the city name, and did not give the specific address and phone number; the contact information only had a 400 switchboard number.

Three notable gaps

At this point, the customer wants to confirm three things: where the company is, how to contact it, and how long it can be demonstrated.

Tell us about ourselves. Our company, Hangzhou Geilixi, previously had two addresses - the office address and the business registration address are not the same, and the telephone is also two sets, one on the official website and one on the enterprise.

A customer searched for us through AI. The AI listed both addresses, but did not say which one was for work. The customer went directly to the registered address and found it empty. Then he made a call and turned off the phone according to the plan. Try another one to get in touch. I almost gave up in the middle, and then he said that he almost moved to the next one.

After this matter, we immediately made up for it: Go to the National Enterprise Credit Information Publicity System and change the registered address to the same as the office address; Baidu, Gaode, and Tencent maps are revised one by one; the official website, enterprise inspection, and third-party platforms are all hung with the same number that can be connected.

After the change, there were two changes: first, the two addresses found by the AI changed to one, and the phone changed to one, so customers no longer need to guess; second, before the address was unified, the AI often did not rank us in the recommendation when making horizontal comparisons - it judged that the information was inconsistent and the credibility was low, and skipped directly. After the unification, the number of times it appeared in the recommendation was significantly higher.

Information gaps in the validation layer, each of which is a loss point:

• The address is wrong.The AI can't tell which one is right, and will also determine that your credibility is low and skip it when ranking. The customer is looking for an address that may have been empty in the past.
• There were several calls, none of them marked "must be able to get through".The one the customer called off, I thought you couldn't get in touch.
• There is no direct conversion portal.There is no appointment demo form, no direct sales call, you can only call yourself if you want to contact, one more loss.

The phone call is not working, the address is wrong, and the reservation entrance can not be found - this connection is broken, and this order is broken.

There is no clever way to verify the layer, three things are in place

1. Each city with a business does the content separately, and the provinces, cities and districts do not fall.
2. The address is written to the house number, and the phone and reservation entrance must be functional. Call once a month and submit the form for verification. Unreachable is the biggest loss point in this layer.
3. Appointment method, implementation cycle update. When the AI searches, it always brings the "latest" and "2026", and the expired information will be reduced.

V. Action Layer: Demonstrate and implement the experience, which will wrap around and affect the AI recommendation

The online bed is not complete. The evaluation generated by the customer's presentation, trial, and implementation will be picked up again by the AI in the second step, and turn around and return to the recommendation results.

Good experience:Professional presentation, transparent quotation, on-time implementation, and after-sales supervision. The customer will renew the contract, will forward the introduction, and will take the initiative to write a success story.

Poor experience:The function of the demonstration blowing is not online, the price signature contract on the Internet has changed, the implementation consultant does not understand the business, and the system has become a recording tool. Customers do not renew contracts, write bad reviews, and tell peers not to use this house.

When we searched for Vendor A's reputation, AI directly listed 4 slots. "Implementation delivery is the biggest variable" and "contracts are usually signed from 2 years" were all real feedback from users. Too bad, the AI will not push you in the comparison stage, or put the shortcomings first. The line is beautiful, the line can't catch up, the word of mouth bites you in turn, and the ranking also falls down.

Sixth and fourth ring loss diagnosis: the top three did not consult, check where your card is

The four rings are broken, and the customer can't walk through the consultation. The top three only means that you have passed the first level.

VII. How to make up: Geo content system based on decision link

Step 1: Find out the customer's questioning path (1-2 weeks, 1 person is enough)

List 20 core industry issues, from "which CRM is good" to "how to book a demo", "how much money to privatize", "is there a hidden charge". If you can't list it, ask sales. The 20 questions that customers ask every day are ready-made lists.

20 questions were searched in each of the 3 AI platforms, and recorded what words and articles the AI took apart each time. 60 results were summarized into a table, categorized by cognition, comparison, and verification, and compared with the existing content to mark the gaps. The "Customer AI Question Path and Content Gaps Table" was produced.

Step 2: Which layer is much missing, and which layer to fill first (4-8 weeks, 1-2 people)

Budget (first-tier cities, 1-2 full-time): 30,000-80,000 manpower for self-constructed teams; 500-2,000 yuan per article for outsourced writing, 50 articles 50-100,000 yuan, channel publishing fees are calculated separately.

Step 3: Check weekly, make up if missing (long-term, 2 hours per week)

Fix 10 core questions, 3 platforms, run a round every week, and focus on four things: which layer is being quoted, which opponent suddenly emerges, which question can't find you at all, and whether the reservation form at the verification layer can still be submitted.

Fix it if you drop it. The cognitive layer dropped 2 supplementary rankings; a certain price segment did not have 1 supplementary price article; a certain city did not have 1 supplementary contact information; the form was broken and it was repaired immediately.

It took 2-4 weeks for AI to start scratching, 6-8 weeks to see the change, and 8-12 weeks for the track of the roll. No movement in the first two weeks, don't stop.

8. Whether it has any effect, only four numbers are recognized

Test once a week, pull the trend at the end of the month, and show it directly to the boss.

If the service provider only gives you a screenshot of "AI mentioned you" in the "manuscript link list", and none of the four numbers follow, there is a high probability that he only made the cognitive layer, and the remaining three layers did not touch.

IX. It can also be used in another industry: the method stays, the dimension is changed

Don't copy the CRM entries, copy the "touch the question path first, and then add content by link hierarchy" set of actions.

Do a quiz first: Go to AI to search for 5 core industry issues. Answer the question correctly, indicating that the customer is already doing their homework with AI and it is worth doing. A piece of "can not answer", indicating that the industry content has not grown, you can take the pit first, but don't expect short-term results.

X. Frequently Asked Questions

Finally: the ranking is the process score, the link is the result

You can be found on all four floors, and the demonstration and implementation can catch the online commitment, which is called Geo.

Before talking to the service consultant, take four questions to go through the program:

1. Can you help me navigate my client's questioning path?
2. Distribute content by Layer 4 link?
3. Verify that my step 3 appointment demo entrance can be submitted properly?
4. Final acceptance, how many manuscripts are sent, or the incidence of core issues?

If you do not know where you are cut off, first check yourself with the table in Section 6 and the process in Section 7. You can also find Geelix to do a free diagnosis of the four-layer link coverage, and give the results within 3 working days.