How Can I Handle Instagram and Facebook Price Comments Without Overwhelming My DMs?

You post a product photo, and the comments start coming in: “How much?”, “Do you have a larger size?”, “Do you deliver to Jeddah?” At the same time, you have private messages, a customer asking about an earlier order, and someone sending a photo to ask for a similar product. You answer what is in front of you while other comments get buried.

In the experience of Rafiq’s founder, the biggest mistake is overlooking comments unintentionally during busy periods. Some of those comments come from people who have just one simple question left before deciding to buy. A question about availability or delivery may be their last step before ordering, but it never reaches you.

A practical solution is to organize the path from comment to useful answer: a clear public reply, a product-specific response in private, and further help if the customer chooses to continue. An AI agent for Instagram and Facebook comments becomes useful when it understands what the person is asking and reduces the store’s reliance on manual monitoring alone.

Why do comments get missed during busy periods?

Private messages constantly compete for your attention. A comment under an older post may be much easier to overlook. As the number of products and posts grows, so does the number of places you need to check. You can be genuinely busy helping customers and still miss a question from an interested buyer.

The same need appears in a discussion about keeping up with price and product-detail comments manually. It illustrates the problem, but it does not establish a lost-sales percentage that applies to every store.

Consider a hypothetical workload: if you receive 100 comments and spend one minute answering each, that adds up to about one hour and 40 minutes. This is an illustrative calculation, not a measurement of Rafiq’s performance. If each answer also requires opening the post and checking the product, a one-minute assumption may not capture the work your team actually does.

“How much?” needs an answer about the right product

Instagram and Facebook comment automation often starts with a saved reply or a private message. But “How much?” does not identify a product by itself. Its meaning depends on the post where the customer left the comment.

If a post shows several items, the answer needs to establish which one they mean. If the image shows an outfit, the customer may be asking about the whole set or just one piece. And if they ask, “Do you have a winter version?”, they are looking for an option that meets their needs, even when the pictured item is summer clothing.

Evaluate your tool’s ability to connect the question with its context. Sending a long list of everything in your catalog leaves the customer to do the searching. A useful answer brings them closer to the right product, or asks a short clarifying question when more than one interpretation is possible.

How does Rafiq handle a comment?

According to the founder, Rafiq posts a customizable public reply, such as:

Thanks for your interest. We’ve sent you a private message.

It then answers privately in a way that fits the comment, whether it is a price question, a compliment, or another inquiry. Rafiq uses the post’s information, examines its image when one is available, and searches for the relevant product to provide a more accurate answer.

The starting point is the customer’s comment together with the post’s context. Someone asking about a pictured item should not have to restart the conversation by explaining which post they mean.

You can customize the public reply to fit your store’s voice. The value of the private conversation shows up in what follows: did the answer address the question, was the product relevant, and could the customer continue without explaining their request again?

A real example: “Do you have a winter version?”

Rafiq’s founder described a children’s clothing store that posted a photo of clothing. A person commented, in Arabic:

Do you have a winter version?

According to the founder, Rafiq searched for winter children’s clothing similar to the product the person meant, answered the customer, and the customer completed an order.

The useful lesson is how the question was handled. The customer did not name a specific catalog item. They referred to the image and asked for a winter alternative. Answering required understanding that request and finding a suitable option.

These are the details the founder confirmed. We do not have the verbatim conversation or figures from which to calculate a conversion rate, so we present it as a founder-reported experience without adding unmeasured results.

An illustrative private conversation

The following exchange was written to show the process. It is not a transcript of the real example above, and the prices are hypothetical:

• Customer: How much is the winter outfit?
• Rafiq: This set is SAR 90. What size do you need?
• Customer: Age four. How much is delivery to Riyadh?
• Rafiq: Delivery is SAR 20, bringing the total to SAR 110. If that works for you, we can complete the order details here in private.
• Customer: Great, I’d like to order it.
• Rafiq: Please send the recipient’s name, contact number, and delivery address in this private chat. Then we’ll review the order details with you. Thank you for your order!

The point is to organize the answers around the customer’s decision: product and size, then price and delivery, then the information needed to complete the order. Personal details stay in the private conversation.

What about “That fabric looks lovely and soft”?

A compliment signals interest and may open the door to a useful question. But the person has not asked to buy yet, so there is no reason to immediately request their address and phone number.

An appropriate private response might be, as an illustrative example: “Thank you! Would you like to know the available sizes or more about the fabric?” That lets the customer decide what matters to them instead of assuming they are ready to order.

Descriptions of the fabric should come from product information. An image can help identify the item, but it cannot by itself establish the fabric’s composition, feel, or suitability for a child’s skin. Missing information needs verification, especially when it affects the purchase decision.

How do you avoid moving the comment overload into your DMs?

Start by preparing information for the products that receive the most questions: price, sizes, colors, material details, and delivery policy. Missing information can lead to another question or require manual intervention.

Next, review the customer’s journey on one post before expanding it. Test a price question, a request for an alternative, a compliment, and a question that could refer to several products. Look at whether the first message is useful and whether the customer needs to repeat themselves.

During a campaign, schedule regular checks of comments that have not been fully handled and conversations that need a person’s attention. Automation reduces the workload; reviewing unresolved cases helps you identify where product information or the response process needs improvement.

Respect the rules for follow-up messages

Moving from a comment to a private conversation is subject to rules that differ by platform and interaction. For Instagram, Manychat’s guide to private replies on comments explains that sending the first private message does not, by itself, open the 24-hour messaging window. The person must interact, for example by replying or clicking a qualifying button.

Make the first message useful and relevant to the question, then continue within the rules that apply to your channel. A comment should not be treated as permission to send a sequence of unrelated offers. Review Facebook’s requirements separately when setting up its workflow.

How do you know whether a tool fits your store?

Begin with something you can observe: comments that previously remained unanswered during busy periods. Then monitor the accuracy of product answers, how many people continue the conversation, and the resulting orders if you can track them.

The number of messages sent is not enough to judge quality. Order creation and successful delivery also need to be tracked separately, particularly for cash-on-delivery stores.

When comparing Rafiq with another tool, test the same post and the same questions in both. Manychat also documents AI replies and conversation goals, so a useful comparison examines how each option performs with your products and customers’ questions, alongside the cost for your actual usage.

Frequently asked questions

Does Rafiq reply publicly and in private?

According to the founder, it sends a customizable public reply, then answers privately based on the comment and the post’s context.

How does it identify the product when someone only asks “How much?”

It uses the post’s information and image, when available, then searches for the relevant product. Test posts containing several products to check how accurately the question is interpreted.

Does every comment turn into an order?

People show different levels of interest, and some only want information. The goal is to provide an answer that helps them decide, without promising that every comment will lead to a purchase.

Should I hand everything over to AI?

Identify situations that need someone from your team, such as complaints, exceptions, and information that requires verification. Test the handoff process before a campaign.

What should I do first?

Choose a product post that receives repeated questions, prepare its information, and test the journey from comment to private reply. You can try Rafiq on that workflow and see how it handles your store’s questions.