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Suggest help articles at the moment they can answer a question: offer a searchable help-center card when the messenger opens, recommend relevant articles after a customer asks something, or use both. Keep suggestions relevant to the customer and their access permissions, and make it straightforward to contact support when an article does not help.
Choose when to show help articles
The two main patterns solve different problems. A search card helps customers who are browsing or want to find an answer themselves. Query-based suggestions respond to a question the customer has already asked. They can work together, but the customer should be able to tell whether they are browsing, receiving a recommendation, or talking to support.
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| Pattern | When it appears | What it is good for | Points to check |
|---|---|---|---|
| Search or suggestion card | When the messenger opens | Inviting customers to browse or search before they type a question | Audience eligibility, article permissions, placement, excluded content, and whether search is optional |
| Question-based recommendations | After the customer asks a question | Offering relevant answers in the context of the customer’s request | Article coverage, supported language, exclusions, and how the customer can continue to support |
| Both patterns | Browsing on open and recommendations after a question | Offering an early self-service route without relying on it to answer every question | Make the two entry points understandable and avoid disrupting an active support workflow |
These are patterns, not requirements shared by all messaging platforms. For example, Intercom documents a public Article search card and a separate Smart Suggestions feature. Zendesk describes article deflection as one possible part of a conversational messaging workflow. The available surfaces and eligibility rules vary by product and client.
Plan the experience before configuring it
Decide what the customer sees first
Choose whether the messenger should lead with a search surface, a question prompt, or a direct path to a person. A search card can be useful when customers arrive with varied needs; question-based recommendations are more focused when the customer has already described a problem. Keep any suggested article clearly labeled and easy to open.
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Decide where suggestions fit in the support workflow
Suggestions may appear before a handoff, within an automated conversation, or as an optional help-center surface. Map what happens when a customer opens an article, returns to the conversation, or still needs help. Zendesk’s Designing your conversational messaging workflow (edited April 29, 2026) recommends choosing the level of automation to fit support goals and workflow needs.
Some configurations can require a customer to search before starting a conversation. Do not enable that behavior without considering whether the content covers the likely questions and whether customers can still find the support route they need. A help suggestion should not become a dead end.
Set up suggestions with relevant, accessible content
- Identify the questions the articles should answer. Use real customer questions and conversation themes to decide what content belongs in the help center. Prefer articles that resolve a specific task or issue over broad, overlapping pages.
- Publish and organize the content. Keep articles current and place them in the collections or help-center structure required by the feature. Intercom’s Smart Suggestions documentation says its described feature needs at least ten live articles, with articles in collections. That threshold is specific to that feature, not a universal rule for in-app messengers.
- Select the entry point and recommendation behavior. Configure an opening search card if customers should be able to browse immediately, question-based recommendations if they should receive contextual results, or both when the product and workflow support them.
- Apply access and audience rules. Check which customers can see the messenger surface and each article. Intercom says customers see only help articles they are permitted to view and documents audience rules for its public Article search card. Do not expose restricted content through a recommendation.
- Review exclusions and language behavior. Exclude content that is irrelevant or inappropriate for the audience when the platform offers that control. Check the language of the customer’s question, available translated articles, and what happens when a language is unsupported. These behaviors are feature-specific; do not assume one feature’s language rules apply to another.
- Test the whole path. Try representative questions, search terms, customer audiences, and languages. Open a suggested article, return to the messenger, and continue to a human-support route. Confirm that suggestions do not interrupt another automation or hide the next step.
- Launch with a clear fallback. Tell customers what the article suggestion is and how to get more help if it does not solve the issue. Keep the support option visible at the point where self-service may fail.
What Intercom and Zendesk document
Intercom: opening card and question-based suggestions are separate features
Intercom’s Enable public article suggestions in the Messenger (June 26, 2026) describes a public Article search card for Messenger Home. It can show up to four suggested articles. Teams can position the card, set audience rules, and exclude articles. Suggestions can be personalized using machine learning, custom data attributes, and visited URLs. The documentation also says users see only articles they are permitted to view.
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Intercom’s separate Let users help themselves with smart suggestions (January 12, 2026) describes recommendations after a customer asks a question, showing up to three articles. Its example connects “How do I invite a teammate?” with an article about adding a teammate, illustrating that recommendations can match intent rather than only identical wording. For the feature described, Intercom specifies English-language conditions and lists situations when recommendations will not appear, including when Custom Answer has participated in the conversation. Those requirements and exclusions apply to that feature; they should not be treated as general messenger standards.
The public card has its own language behavior: Intercom says localized help may match the browser language, while unsupported languages fall back to the Help Center default. Do not assume the Smart Suggestions language conditions and public-card fallback are interchangeable.
Zendesk: article suggestions can be part of a messaging workflow
Zendesk’s About conversational support with messaging (edited June 4, 2026) describes conversational support across messaging. Its Answer Bot developer documentation, Running the Answer Bot engine, describes query-based article recommendations of up to three at a time, followed by a prompt asking whether the article solved the issue. Zendesk’s Web Widget and SDK capabilities documentation describes multiple widget and SDK surfaces with platform-specific limitations. The exact client experience therefore depends on the surface and SDK; the documentation does not establish one universal behavior for every web or mobile messenger.
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Keep the route to a person clear
Self-service is useful only when customers can recover from a mismatch. Make it possible to return from an article to the conversation, explain how to continue if the answer is not useful, and avoid making an article view appear to be a successful resolution by itself. If your workflow requires searching before contact, check the content and handoff experience with realistic questions before applying that requirement broadly.
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Track the steps that distinguish a useful answer from an abandoned or unresolved interaction. Depending on the platform, useful signals include:
- Whether the search card or an article recommendation was shown.
- Whether the customer opened an article and, where available, said it helped.
- Whether the customer returned to the conversation or started a human conversation.
- Searches with no useful result and conversations that remain unresolved.
Intercom’s Conversational support report defines “Self-serve sessions resolved” as sessions in which a customer viewed articles or received bot support and did not start a human conversation. Treat that as Intercom’s operational definition, not proof on its own that the customer’s problem was fully resolved. Review conversations and recurring questions to find missing, outdated, or unclear articles.
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Choose a pattern that fits your messenger
Compare the behaviors that affect both the customer and the support team before rollout:
| Decision | What to establish |
|---|---|
| Timing | Whether help appears on messenger open, after a question, or at both points |
| Matching | Whether results are a curated list, a search result, or recommendations based on a customer’s question and available context |
| Eligibility | Audience rules, article permissions, minimum-content requirements, and feature-specific exclusions |
| Language | Supported question languages, translated article coverage, and fallback behavior |
| Handoff | Whether suggestions are optional, whether search is required, and how a customer can reach a person |
| Measurement | Article impressions or opens, helpfulness feedback, human conversations, and the platform’s definition of self-service resolution |
| Client support | Which web, iOS, Android, or other widget and SDK surfaces support the intended experience |
Validate details against the product documentation for the account, plan, feature cohort, and client version you will deploy. Product names, capabilities, and eligibility may change.
Frequently Asked Questions
Can suggested articles be shown only to certain customers?
That depends on the platform and the feature. Intercom documents audience rules for its public Article search card; apply access rules to the articles themselves as well as to the messenger surface.
Does a customer need to type an exact article title to get a useful recommendation?
Not necessarily. Intercom’s documented example maps a question about inviting a teammate to an article about adding a teammate, rather than requiring the question and title to use identical wording.
What if the messenger does not support the article experience I want on mobile?
Check the documentation for the specific widget or SDK and client version you plan to use. Zendesk documents platform-specific widget and SDK capability limitations, so a web behavior should not be assumed to work identically in every mobile app.
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