Chatbot für E-Commerce im Jahr 2026: Wie Online-Shops KI-Bots nutzen, um Warenkörbe wiederherzustellen, Fragen zu beantworten und den Umsatz zu steigern

Ein Chatbot für den E-Commerce verdient sein Geld an drei Stellen: wenn ein Käufer zögert, wenn ein Warenkorb verlassen wird und wenn der Support zu einem Konversionsblocker wird. Alles andere ist sekundär.

Die nützlichen Versionen von 2026 sind keine generischen Chatblasen mit ein wenig KI-Politur. Sie wissen, was im Warenkorb ist, sie können den Bestellstatus abrufen, sie können das richtige Produkt empfehlen, anstatt einen zufälligen Bestseller, und sie übergeben das Gespräch an eine Person, bevor der Kunde in einer schlechten Schleife gefangen wird.

Das ist der Rahmen für diesen Artikel. Ich habe öffentliche Preisseiten, Hilfedokumente, Marktplatzangebote und Trendberichte von 2026 am 12. April 2026 von MessengerBot, Shopify, Tidio, Gorgias, ManyChat, WooCommerce, Baymard und Zendesk überprüft. Wenn Sie zuerst einen breiteren Marktüberblick wünschen, beginnen Sie mit unserem plattformübergreifenden E-Commerce-Chatbot-Leitfaden. Dieses Stück ist enger und praktischer: wie man einen Chatbot für den E-Commerce auswählt und implementiert, ohne Ihren Shop in einen Stapel von disconnected Apps zu verwandeln.

Warum ein Chatbot für den E-Commerce 2026 wichtiger ist als vor einem Jahr

Der einfachste Grund ist immer noch der schmerzhafte: Geschäfte zahlen weiterhin für Traffic, den sie nicht konvertieren. Baymards neuester Benchmark zur Warenkorbabbruchrate setzt die durchschnittliche dokumentierte Abbruchrate bei 70.22%, aktualisiert im September 2025. Baymards 2025er Abbruchanalyse ist sogar noch nützlicher für die Planung, da sie die Reibung hinter der Zahl zeigt: 39% von Käufern brechen ab, weil die zusätzlichen Kosten zu hoch sind, 21% weil die Lieferung zu langsam ist, 19% weil sie der Seite nicht mit ihren Kartendaten vertrauen, 19% weil die Seite möchte, dass sie ein Konto erstellen, und 18% weil der Checkout zu lang oder kompliziert erscheint (Baymard).

Das sind sowohl Gesprächs- als auch Designprobleme. Versandkosten, Lieferzeiten, Größenzweifel, Produktanpassung, Zahlungsvertrauen, Rückgabebedingungen und Verwirrung beim Checkout sind genau die Fragen, die ein guter Bot beantworten kann, während der Käufer noch entscheidet, anstatt nachdem der Tab geschlossen wurde.

Die Erwartungen haben sich ebenfalls verändert. Die CX-Trends-Studie 2026 von Zendesk besagt 74% dass Verbraucher jetzt erwarten, dass der Kundenservice verfügbar ist 24/7 weil KI existiert, und 86% sagen, dass Reaktionsfähigkeit und genaue Lösungen die Kaufentscheidungen stark beeinflussen (Zendesk CX Trends 2026, Zendesk Nachrichtenraum). Wenn Ihr Geschäft den Chat immer noch als nettes Widget für die Bürozeiten behandelt, arbeiten Sie unter den Erwartungen der Kunden, bevor das Gespräch überhaupt beginnt.

Es gibt einen zweiten Wandel im Jahr 2026, der ebenso wichtig ist: Der E-Commerce-Stack wird standardmäßig konversational. Der Conversational Commerce-Bericht von Gorgias für 2026 sagt, dass KI bereits 31% von Kundeninteraktionen für E-Commerce-Marken, die seine Plattform nutzen, bearbeitet und voraussichtlich innerhalb von 47% zwei Jahren erreichen wird. Der gleiche Bericht besagt, dass 79% von Marken berichten, dass der KI-gesteuerte Conversational Commerce den Umsatz und die Kaufquoten erhöht hat, während Gorgias-Kunden mehr als 350 Millionen Käufergespräche im Jahr 2025 hatten und fast 10 Millionen davon in einen Kauf umgewandelt wurden (Gorgias-Bericht, Gorgias Trendzusammenfassung).

Lieferantenberichte erfordern immer ein wenig Skepsis, aber die Richtung ist schwer zu übersehen. Geschäfte fragen nicht mehr, ob Chat in den E-Commerce gehört. Sie fragen, welcher Teil des Trichters zuerst konversational sein sollte: Entdeckung, Warenkorberholung, Unterstützung nach dem Kauf oder Wiederholungskäufe.

Die ehrliche Antwort ist, dass nicht jeder Shop am ersten Tag einen riesigen KI-Einkaufsagenten benötigt. Die meisten Geschäfte brauchen einen Chatbot für den E-Commerce, der zuerst ein teures Leck behebt, den ROI nachweist und dann erweitert. Das bedeutet normalerweise verlassene Warenkörbe, Produktempfehlungen, Bestellverfolgung oder Retourenbearbeitung.

Was ein E-Commerce-Chatbot tatsächlich tun sollte, bevor Sie für einen bezahlen

Der einfachste Weg, Software zu überkaufen, besteht darin, nach der Anzahl der Funktionen zu kaufen. Der bessere Weg ist zu fragen, welche Aufgabe der Bot erfüllen muss, welche Geschäftsdaten er benötigt und welche Zahl er im Unternehmen bewegen sollte. Wenn Sie diese drei Fragen nicht beantworten können, kaufen Sie keinen Chatbot für den E-Commerce. Sie kaufen Hoffnung.

This is why the phrase Shopping-Bot can mean very different things. For one merchant it means a Messenger sales flow that nudges a buyer back into checkout. For another it means an on-site AI assistant trained on WooCommerce product data. For a larger brand it means an AI agent inside a help desk that can answer pre-sale and post-sale questions while also editing orders or triggering returns.

Here is the practical rule: if the bot does not have your product data, your fulfillment data, and a visible human handoff, it will struggle the moment the conversation becomes commercially important. If you are still in the build phase, Durchsuchen Sie unsere Tutorials before you automate five workflows at once. Launching one well-instrumented flow beats launching a full fake-AI concierge every time.

Best ecommerce chatbot platforms in 2026 by store type, not hype

Pricing and product details below were checked against public pages on April 12, 2026. I am not ranking these platforms as generic AI tools. I am comparing them for actual ecommerce work: cart recovery, product discovery, support deflection, and revenue-driving conversations.

Quellen: MessengerBot-Preise anzeigen, Shopify Inbox, Shopify Inbox App Store listing, MessengerBot-Preise anzeigen, Gorgias pricing, Gorgias billing docs, ManyChat 2026 plan guide, ManyChat Pro plan details, ManyChat pricing page, Amaya Chatbot AI PRO, AI Product Recommendations, Woo Product Recommendations.

Two observations matter here. First, the cheapest tool is rarely the cheapest system once you include overages, extra seats, AI usage, or the second app you need because the first one only solved half the problem. Second, platform fit matters more than brand awareness. Shopify Inbox is excellent if you want native Shopify chat. It is the wrong answer if most of your selling happens through Messenger. MessengerBot makes sense if Facebook conversations and WooCommerce sync are central. It is not the best first buy if your real problem is a support operation that already behaves like a ticket queue.

ManyChat deserves a special note because its pricing is in transition. ManyChat’s help center says it introduced a new pricing model on 2. März 2026 with Free, Essential, Pro, Business, and Advanced plans for newer accounts, and its Pro plan page lists $39 per month for monthly billing with 2,500 active contacts. At the same time, ManyChat’s public pricing page crawler snapshot still shows Pro starting at $15 pro Monat and warns that plan availability varies by region and account age. That is not a deal-breaker. It just means you should verify the exact bill before you compare it with flat-price tools.

If your shortlist now includes MessengerBot, the cleanest next step is to MessengerBot-Preise anzeigen and compare its flat public tiers against the more variable contact-, ticket-, or automation-based models above.

How to choose the right sales chatbot for your store architecture

This part is where most ecommerce teams make a category mistake. They compare a website support bot, a Shopify-native chat tool, a Messenger marketing platform, and a WooCommerce recommendation plugin as if they all solve the same job. They do not.

Use this framework instead:

• Choose Shopify Inbox first if you run a Shopify-only store, need a free starting point, and want native cart and order context without adding another system immediately. Shopify says Inbox is free, and its App Store listing says faster responses can improve conversion by up to 69% while 70% of Inbox conversations are with customers making a purchase decision (Shopify Inbox, Shopify App Store).
• Choose Tidio first if your site is the main selling surface and you want one tool that handles live chat, AI support, order status, and product recommendations across Shopify or WooCommerce. Tidio’s current pages are unusually clear about Shopify order-status actions, WooCommerce product cards, and AI product recommendations for WooCommerce (Tidio Shopify order status, Tidio WooCommerce integration, Tidio WooCommerce recommendations).
• Choose Gorgias first if your support team already thinks in tickets, macros, SLAs, and post-purchase workflows. Gorgias is often the right buy when order edits, refunds, returns, and omnichannel support are already complex enough that a basic chatbot would just create a second inbox.
• Choose MessengerBot first if Facebook Messenger is a true sales and support channel, not an afterthought, and your store runs on WooCommerce or sells through Meta plus website chat together. MessengerBot’s public pricing page is explicit about abandoned cart recovery, one-click WooCommerce sync, website chat, JSON API + Zapier, and zero revenue share for ecommerce stores (MessengerBot-Preise anzeigen).
• Choose ManyChat first if your growth engine is social DM selling: Instagram comments, story replies, click-to-message ads, and re-engagement sequences that eventually push buyers into checkout.
• Choose a WooCommerce-native AI plugin first if your main bottleneck is on-site product discovery, not multichannel support. A small WooCommerce store with a complex catalog may get faster value from Amaya or AI Product Recommendations than from a larger service suite.

The real decision is not “Which ecommerce chatbot has the most AI?” It is “Where does buying friction show up in this store, and which software sits closest to that friction?” Get that right and even a modest plan pays back quickly. Get it wrong and you end up paying for features that live in the wrong channel.

The abandoned-cart recovery flow that works without training shoppers to wait for coupons

Most cart-recovery setups fail for one of two reasons. Either they fire a single generic reminder and call it strategy, or they jump straight to a discount and train buyers to abandon on purpose. A better ecommerce chatbot sequence mirrors how hesitation actually develops.

Baymard’s 2025 abandonment reasons help here. Extra costs, delivery timing, trust, forced account creation, and a complicated checkout are the major friction points. That means the bot should not just remind the shopper that a cart exists. It should resolve the most likely objection at the right moment.

The first message should feel like recovery, not persuasion. Something as simple as “You left this in your cart. Want to pick up where you stopped?” is usually enough. At one hour, many shoppers were interrupted, not unconvinced.

The second message is where a Verkaufs-Chatbot actually earns its keep. If you sell apparel, answer sizing. If you sell supplements, answer compatibility or routine questions. If you sell furniture, address delivery timing and returns. If you sell electronics, handle compatibility anxiety before it turns into comparison shopping on another site.

The third message is where you make a disciplined decision. Either the economics support a small incentive, or the shopper needs a human answer. Do not send a fourth, fifth, and sixth generic reminder and pretend persistence is strategy. A strong three-step flow is usually enough to tell you whether the cart was recoverable.

Tidio’s cart tracking guidance is useful here because it separates Shopify’s built-in path from non-Shopify implementation. Shopify users can enable abandoned-cart tracking directly in Tidio settings, while non-Shopify stores add a short script and then attach the flow (Tidio abandoned cart tracking). Shopify’s own help center also makes an important distinction: abandoned checkout automation applies after the customer has entered checkout details, not to every anonymous cart browser, and its default template sends an email after a wait period unless you change it in Flow or the new Messaging automation (Shopify abandoned checkout automation, Shopify Flow trigger).

That difference matters because a chatbot for ecommerce can cover both layers. It can help in-session before the shopper vanishes, and it can follow up after the checkout is abandoned if you have the right consent and identity path.

A quick launch checklist:

• Suppress buyers the moment checkout completes.
• Segment by cart value so high-margin and low-margin buyers do not get the same offer.
• Measure recovered revenue, not just clicks or replies.
• Keep shipping, returns, and sizing answers one tap away inside the conversation.
• Test one variable at a time: timing, incentive, or objection-handling copy.

How AI product recommendations raise order value without feeling random

Most stores say they use recommendations when what they really have is a generic “you may also like” block under the product page. A real ecommerce chatbot does something harder and more useful: it asks, narrows, compares, and explains.

This matters most when the shopper is thinking one of these thoughts:

• I do not know which version fits me.
• I want the right accessory, not a random add-on.
• The product I wanted is out of stock, so what is the closest substitute?
• How much more do I need for free shipping?

Shopify Inbox already supports product links, cart insight, and discount sharing during chat, which is enough for lightweight assisted selling (Shopify Inbox). Tidio now has a dedicated WooCommerce product-recommendation feature that lets Lyro recommend products, compare alternatives, and suggest complementary items based on the conversation (Tidio WooCommerce recommendations). On the WooCommerce-native side, AI Product Recommendations positions itself as an AI shopping assistant plus recommendation engine, and Woo Product Recommendations focuses on smart upsells, frequently bought together logic, and rule-based placement across cart, checkout, and thank-you pages (AI Product Recommendations, Woo Product Recommendations).

The pattern that works is simple:

1. Ask two or three qualifying questions. Fit, budget, style, usage, compatibility, or gift intent usually gets you enough context.
2. Show no more than three products at a time. The bot should reduce decision load, not recreate the category page.
3. Explain the recommendation. “Best for warm weather and wide fit” converts better than a bare SKU.
4. Use bundles and thresholds intelligently. Accessories, refills, and threshold nudges work when they feel useful, not forced.
5. Track assisted orders separately. Recommendation lift usually appears in chatbot-assisted orders first, not in the whole store average overnight.

This is where a Shopping-Bot becomes more than automation. It acts like a competent in-store associate. It does not ask the buyer to search harder. It helps them choose faster.

One more practical point: if your catalog is tiny and obvious, a lightweight rule-based flow may beat an expensive AI stack. The bigger the catalog and the more pre-sale questions your team fields, the more valuable AI-guided recommendations become.

Order tracking and returns automation usually pay back faster than flashy AI

If your inbox is full of “Where is my order?” and “Can I change my shipping address?” questions, you do not need a futuristic AI vision before you automate. You need a clean self-service layer and a reliable handoff path.

Shopify gives you a solid baseline. Shopify Inbox includes a default Track my order instant answer, and Shopify’s help center shows that customers can already receive order-status updates through the store’s order status page, emails, and the Shop app once tracking exists (Shopify Inbox instant answers, Shopify order tracking). Tidio adds a Shopify smart action that can verify shoppers through email, order ID, and zip code, then return payment, fulfillment, purchased items, and tracking details in chat. Its help docs also note that Growth-plan users can cancel orders, submit refunds, and change the shipping address directly inside Tidio for eligible Shopify orders (Tidio order status action, Tidio Shopify order management).

Gorgias goes further because it is designed as an ecommerce support operating system, not just a chat widget. Its current pricing page and billing docs position AI Agent around pre-sale and post-sale FAQs, returns and refunds, order edits, subscriptions, and product recommendations, with automation billed by resolved interactions on top of helpdesk usage (Gorgias pricing, Gorgias billing docs).

The ROI math is not complicated. Suppose your store handles 1,000 support conversations a month, und 55% are repetitive order-status, shipping-window, or return-policy questions. That is 550 conversations. At a blended handling cost of $4 each, that queue costs around $2,200 a month. If the bot fully automates just 60% of that repetitive slice, you remove 330 manual touches or about $1,320 in monthly handling cost before you even count faster response times.

That is why order tracking is usually the first support automation I would ship after cart recovery. It is easy to test, easy to verify, and easy for a customer to trust when the answer is accurate.

Where stores go wrong is trying to automate emotionally loaded exceptions with the same confidence. Wrong item, damaged item, high-value refund dispute, and fraud suspicion should not stay in the bot lane for long. The good pattern is simple triage: collect the order number, identify the issue type, answer the easy part, then move complex cases to a person with all the context attached.

How to set up a chatbot for Shopify without overbuilding the stack

Shopify is the cleanest environment to start in because the native tools are good enough to prove value before you buy more software. That matters. A lot of merchants jump straight to a third-party platform when Shopify already gives them enough signal to find out whether chat is moving revenue.

1. Start with the first job, not the first app. Pick one of these: pre-purchase Q&A, abandoned checkout recovery, order tracking, or product guidance. If the bot has no clear job, it becomes a polite distraction.
2. Install Shopify Inbox and turn on the basics. Shopify positions Inbox as a free business chat app built into the admin, with product links, discount sharing, AI-generated answers, and message classification (Shopify Inbox).
3. Configure instant answers before you touch AI. Your baseline set is usually shipping time, return policy, order tracking, and one product-fit question. Shopify’s instant-answer docs note that the Track my order option is included by default (Shopify Hilfezentrum).
4. Use abandoned checkout automation for the checkout layer. Shopify’s current docs say the new abandoned checkout automation lives in the Shopify Messaging app, defaults to a 10-hour wait on a second automation, and is limited to Online Store and Buy Button channels (Shopify Messaging automation).
5. Add a website-first specialist only when the native layer is obviously thin. Tidio is the most balanced next step for many Shopify stores because it gives you order-status actions, cart flows, AI replies, and support structure without immediately forcing a full helpdesk migration.
6. Move to Gorgias when support operations become the harder problem. If agents need deeper routing, macros, revenue attribution, order operations, and omnichannel ticketing, this is usually the point where Inbox stops being enough.
7. Test every flow on mobile. Most Shopify traffic is still mobile-heavy. A chatbot that blocks product media, hides the add-to-cart button, or demands too much typing on a phone is hurting the store while pretending to help it.
8. Instrument assisted revenue and support deflection separately. Do not use one dashboard number to judge a sales flow and a support flow. Track them differently.

There is also a 2026 Shopify-specific reason to clean up product data now instead of later. Shopify’s help center says its agentic storefront experience for ChatGPT is available to eligible stores today, while other AI channels such as Microsoft Copilot and Google AI Mode or Gemini remain in early access depending on eligibility and settings. In other words, your product feed and policy data are becoming conversation inputs for AI channels outside your site, not just inside it (Shopify agentic storefronts).

That does not mean every Shopify merchant should rush into AI-channel commerce. It does mean messy product titles, weak variant data, vague shipping rules, and outdated FAQ content are becoming more expensive problems than they used to be.

How to set up a chatbot for WooCommerce when your store sells through both the site and Messenger

WooCommerce is more flexible than Shopify, but that flexibility comes with more decision-making. There is no single native answer. You choose between website-first chat, Messenger-first automation, or a hybrid stack that combines on-site product guidance with social conversations.

If your WooCommerce store mainly sells on-site and the main friction is product discovery, Amaya Chatbot AI PRO and AI Product Recommendations are interesting because they stay close to the catalog. Amaya positions itself as a product-catalog trained AI chatbot with a WooCommerce-native widget and a $49 per year Pro tier. AI Product Recommendations lists $39 per year and combines an AI shopping assistant with personalized and upsell recommendations. Woo’s own Product Recommendations extension lists $99 per year and focuses on smart upsells, frequently bought together logic, analytics, and placement across product, cart, checkout, and thank-you pages (Amaya Chatbot AI PRO, AI Product Recommendations, Produktempfehlungen).

If your WooCommerce store sells through Facebook Page messages, click-to-Messenger ads, or ongoing Messenger conversations, the better fit is often MessengerBot. Its public pricing page explicitly includes abandoned cart recovery tools, website chat, one-click WooCommerce integration, JSON API + Zapier, Google Sheets sync, and zero revenue share for ecommerce stores (MessengerBot-Preise anzeigen).

This is the build order I would use for most WooCommerce stores:

1. Clean the catalog first. Product titles, variants, attributes, shipping details, and policy pages need to be usable by both the bot and the customer.
2. Decide whether the primary conversation starts on the website or in Messenger. That one choice will shape the software stack more than any AI feature checkbox.
3. Connect the catalog and test product answers. If the bot cannot answer a basic product-fit question correctly, do not turn it loose on cart recovery yet.
4. Wire abandoned-cart or cart-hesitation events. The follow-up should know which product was viewed or left behind.
5. Add order-status and policy shortcuts. Even a sales-oriented bot needs a post-purchase layer or the same buyers come back to ask shipping questions later.
6. Test human handoff in the exact edge cases that create refunds. Wrong size, broken item, late delivery, exchange request, and payment failure are the minimum set.

MessengerBot is especially strong in the WooCommerce-plus-Meta scenario because it reduces the number of tools you need to wire together just to cover website chat, Messenger engagement, cart recovery, and comment automation. If your store has outgrown a starter Meta workflow and needs more pages, widgets, or multichannel headroom, this is usually the point where you Upgrade to MessengerBot Pro instead of stacking a second platform on top of the first.

The mistake to avoid is mixing a website-only AI plugin with a Messenger-led sales motion and expecting one of them to behave like the other. They are solving different parts of the funnel. Pick the conversation origin first, then layer the second system only if the numbers justify it.

The ROI model a chatbot for ecommerce needs to pass before you scale it

Store owners often hear that chatbots boost sales, increase conversion, lift order value, and reduce support costs all at once. Sometimes they do. The problem is that teams hear those outcomes as a promise instead of a stack of smaller effects that need to be measured separately.

Use this model instead:

Monthly chatbot value =
+ recovered cart revenue
+ incremental assisted-order revenue
+ repeat-purchase revenue influenced by chat
+ support cost avoided
- software fees
- usage fees
- setup and maintenance time

Now run conservative numbers.

Then add realistic chatbot effects:

Against a $54,600 revenue base, that is a meaningful lift without using fantasy assumptions. Even if software and message fees cost several hundred dollars a month, the payback is still attractive.

The biggest modeling mistake is mixing store-wide results with chatbot-assisted results. If a recommendation flow lifts AOV by 20%, that usually means assisted orders, not the whole store overnight. If a cart sequence converts at 18%, that means reachable shoppers with identity and permission, not every anonymous visitor who vanished. Honest math beats inflated screenshots every time.

It is also worth separating revenue from cost avoidance. A support-heavy store may justify a chatbot mostly through ticket deflection and faster service. A DTC brand running paid social may justify it mostly through recovered carts and pre-sale guidance. Same category, different ROI story.

The mistakes that make ecommerce bots feel smart in demos and useless in production

The fastest way to waste money on a chatbot for ecommerce is to confuse a polished interface with a working system. Production failures are usually not model failures. They are setup failures.

• Buying AI before fixing product and policy data. If your catalog is messy, the bot will be messy faster than a human.
• Using the same script for pre-sale chat and post-purchase support. Product guidance, order tracking, and return triage are different jobs.
• Leading every recovery flow with a discount. That conditions customers to abandon in order to get paid for waiting.
• Hiding the human handoff. Good bots reduce workload. Bad bots block access to help.
• Measuring vanity metrics. Opens, clicks, and chat volume are not the same as recovered revenue, assisted AOV, or true deflection.
• Ignoring mobile UX. If the widget covers product images or checkout buttons, you are paying to reduce conversion.
• Automating sensitive exceptions too aggressively. Damaged orders, chargeback risks, or high-value disputes need a person quickly.
• Not clarifying billing triggers. Contacts, tickets, conversations, and AI resolutions are four different pricing models with four different scaling risks.

This is why small, well-scoped launches keep outperforming broad AI rollouts. Start with one flow that maps cleanly to revenue or support savings. Get the instrumentation right. Then expand.

When MessengerBot is the right ecommerce chatbot to implement first

MessengerBot is not the right answer for every store. It is the right answer when your store actually sells through Meta conversations, needs WooCommerce sync, or wants website chat plus Messenger automation under one roof without moving straight into a ticket-priced helpdesk.

The public MessengerBot pricing page is unusually specific about the things ecommerce operators care about: abandoned cart recovery tools, website chat, one-click WooCommerce integration, JSON API + Zapier, payment-provider support, visual flow building, and zero revenue share for ecommerce stores. The Premium plan is listed at $19.99 pro 30 Tage, and the Pro plan at $49.99 pro 30 Tage, with higher limits on pages, widgets, and broader capabilities (MessengerBot-Preise anzeigen).

That makes MessengerBot especially practical for three situations:

• WooCommerce stores that want Meta plus website chat in one system.
• Facebook Page driven businesses where Messenger is already a real support and sales inbox.
• Teams that prefer public flat pricing over ticket or automation resolution billing.

If that sounds like your setup, use the next step that matches your maturity level. If you are still comparing tiers, MessengerBot-Preise anzeigen. If you want implementation detail before you buy anything, Durchsuchen Sie unsere Tutorials. If you are already running enough stores, pages, or widgets that the starter tier is tight, Upgrade to MessengerBot Pro. And if you build ecommerce chatbot systems for client stores or recommend tools as part of your agency work, Treten Sie unserem Affiliate-Programm bei so referrals are structured instead of informal.