Drift Chatbot Alternatives for Support and Sales

Chatling

Best for: Teams looking for an AI chatbot with knowledge-based support and a route to human agents. The evidence also describes multiple channels and an agent-assist tool, which drafts replies, summarizes chats, and finds answers from a knowledge base.

Key strengths: Chatling's handoff can show an AI-generated summary to the human agent, and the evidence says handed-off conversations can be distributed among eligible agents. Its listed channels include website, WhatsApp, Telegram, Messenger, and Instagram. The pricing evidence separates AI credits, agents, seats, and knowledge-base limits, so teams can see which dimensions may grow with use.

Trade-offs: Credit consumption depends on the model, and each AI response uses credits. Third-party pricing material gives different free-plan limits, so do not rely on a single reported allowance without checking the current offer. Extra credits, agents, seats, branding removal, and a custom domain are listed as possible add-ons in one estimate. A low headline price may not represent the cost of the configuration your team needs.

Pricing model: Evidence describes a free plan and paid tiers, including estimates billed yearly, plus monthly add-ons. Because credit use varies by model and each AI response uses credits, estimate how your expected conversations fit the current plan before comparing the total bill.

Crisp

Best for: Startups considering an omnichannel messaging product with workspace-based pricing, as characterized by a third-party overview.

Key strengths: The available summary highlights omnichannel messaging and workspace pricing rather than per-agent pricing. That model may be worth assessing if the team wants to consider cost at workspace level instead of counting individual agents.

Trade-offs: The evidence does not establish the current details of Crisp's AI answer behavior, knowledge sources, live-chat limits, or human handoff. Those are important questions for a support team comparing grounded answers and ticket ownership, so assess them directly rather than assuming they match another tool's workflow.

Pricing model: A third-party report lists a free option and a cheapest paid Mini plan at $45 per month, checked October 15, 2026. Higher plans, add-ons, and taxes cost extra according to the pricing note. Treat the figure as a reported entry price, not a complete estimate for your team.

Landbot

Best for: SMBs and marketers who want a no-code chatbot builder with a visual, drag-and-drop approach.

Key strengths: The available overview identifies the visual builder as Landbot's differentiator. That points to a fit for teams designing conversational experiences themselves rather than choosing solely on the basis of a support inbox or AI knowledge workflow.

Trade-offs: The evidence does not establish current channel coverage, AI grounding, supported knowledge inputs, human handoff, or usage limits. A category description is not enough to determine whether Landbot will cover order questions, support escalation, or a particular customer-service workflow. Ask for a demonstration of the exact conversation path your team needs.

Pricing model: A third-party summary reports a free option and paid plans from €40 per month. Before deciding, compare the actual plan, its usage terms, and the limits included at that entry price with what your team needs.

Chatbase

Best for: Teams considering a chatbot trained on custom data, based on the brief overview available for Chatbase.

Key strengths: The summary identifies custom data-trained AI as its fit. That makes it a name to evaluate when the main problem is answering questions from business-specific material.

Trade-offs: The evidence does not establish Chatbase's current pricing, channels, knowledge inputs, handoff workflow, citation behavior, or plan limits. Those details matter if the chatbot needs to route uncertain questions to a human or operate as part of a shared support desk. Compare a real visitor question and escalation path, not just the general promise of custom-data answers.

Pricing model: No price or pricing mechanics are established here. Request the current plan details and compare the total cost against expected usage and the support workflow you need.

momo

Best for: Store owners and startup support leads who want customer answers grounded in their own content, with unanswered questions handed to a team inbox.

Key strengths: It retrieves relevant passages from business knowledge, drafts an answer, and checks the draft against those sources. When confident, it sends the answer with citations; when not, it says it is not sure and opens a ticket. Knowledge can include a website crawl, PDFs, Word files, plain text, and Q&A pairs. A human response can later be saved as approved knowledge through the Teach step.

Trade-offs: This is a support-desk fit, not evidence of a replacement for Drift's sales qualification, lead routing, or CRM workflows. Shopify is in preview, and Shopify order lookups or actions are not established. Choose it for the customer-support workflow described, not for sales functionality that has not been established.

Pricing model: Flat EUR plan fees with included AI conversations, no per-resolution fee, and no credit packs. The helpdesk inbox is included on every plan.

Choose by the work your team needs done

Start with the conversation, not the chatbot label. A visitor asking whether a product is available needs a different workflow from a B2B prospect being qualified and routed to a sales representative. A support tool may handle repeated questions and hand unresolved issues to a shared inbox; a sales platform may be built around qualification, routing, pipeline context, and meetings. Those jobs can overlap, but the evidence here does not establish that these products are interchangeable.

For a small store

List the customer questions that arrive repeatedly: delivery information, returns, product details, or other policies. Check whether the tool can use the content where those answers live, and what happens when it cannot answer safely. Ask how a human receives the conversation and what details are collected before the handoff. For ecommerce workflows, verify order-specific functionality separately; a chatbot trained on policy content should not be assumed to look up or change an order. Compare the predictable plan fee with the included usage and any model-based credits or add-ons.

For a startup support team

Compare the sources the AI can use, the form of citations or answer checks, the channels available to customers, and how a teammate takes over. If several people share the work, clarify the difference between seats, agents, and workspace-level pricing. For tools where credit use varies by model, estimate usage with the models you plan to use rather than comparing only headline plan prices. Crisp's reported workspace pricing and Chatling's credit mechanics are different billing considerations; the evidence does not establish enough detail to declare one less expensive for every team.

For a B2B sales team

Prioritize lead qualification, routing, CRM context, and the availability of sales representatives. Drift is described as a fit for medium-to-large B2B teams with complex sales pipelines, while its public price evidence is largely estimates and its standard pricing is not published. Before replacing a sales-oriented workflow with a support-first inbox, map who receives each lead and what context must travel with it. Do not switch based on chatbot answers alone if routing and pipeline work are central to the team.

Make the final comparison practical

Take a real customer question and a real escalation scenario to each vendor. Check the answer, the source behind it, the point at which a human steps in, and the total billing structure. For a support desk, include the inbox and team handoff in the test. For a sales tool, include the lead path and representative workflow. This makes the choice about the work the team needs, not a list of feature names.