Customer storysmava logo

27,000 loan tickets a month, sorted and drafted in German

smava and Finanzcheck share one Zendesk. Three eesel agents work it: one categorises every ticket, one drafts the reply from the macro library, and one per brand prepares the customer-ready answer.

Industry
Consumer finance, online loan comparison
Based in
Berlin, Germany
With eesel since
December 2024
Working with
Tanja van Treel, Head of Customer Success at smava
27,000Zendesk tickets handled in a month8 Aug to 8 Sep 2026, smava and Finanzcheck together
14,600tickets categorisedlanguage tag, reply eligibility and category, written into Zendesk fields
15,300draft replies preparedabout 1,100 of them by the two per-brand reply agents
820macros and help center articles it drafts fromsynced from Zendesk, kept apart by brand
smava.de
smava website
How it runs

What happens when a customer writes to smava

  1. 1
    A ticket arrives in Zendesk

    The categorisation agent fires on every smava or Finanzcheck ticket.

  2. 2
    eesel tags and categorises it

    It tags the language, checks eligibility and sets one category.

  3. 3
    The drafting agent finds the macro

    It drafts the matching CS::Mail macro word for word, placeholders filled.

  4. 4
    Eligible tickets get a customer-ready reply

    Tickets with no advisor get a reply prepared, and eesel never sends it.

  5. 5
    People take it from there

    Agents approve the draft or ask @eesel for another macro.

Connected integrations

  • Zendesk

Agents at work

  • Categorisation Agent (Live)14,573 runs in 30 days
  • Zendesk Drafting Agent (Live)12,163 runs in 30 days
  • Public Reply Agent Smava (Live)779 runs in 30 days
  • Public Reply Agent FC (Live)306 runs in 30 days

The company

smava is a Berlin comparison platform for German consumer credit, founded in 2007. It compares offers from more than 20 partner banks for loans between 1,000 and 120,000 euros. In 2021 it acquired Finanzcheck, a Hamburg loan marketplace. The two brands run customer support out of one Zendesk.

Visit smava at smava.de

The problem

About 27,000 tickets a month come into that Zendesk, almost all in German, from two brands with their own macros and advisors. Every ticket needs a category from a fixed list written into a Zendesk field, and a reply that says what the approved macro says. This is regulated finance, so wording matters: a reply that promises something the team will do, names a competitor, or guesses at a loan the company can no longer see does harm.

Some tickets belong to a person from the start. A customer who already has a credit advisor should hear from that advisor, not from an automatic reply.

How it runs

smava has run eesel on its Zendesk since December 2024; the current three-agent setup went live in June 2026. eesel works from about 820 macros and help center articles synced from Zendesk, a category mapping document the team wrote, and smava’s banking wiki. Each agent has one job and a list of things it must never do.

  • Categorisation agent. On every new ticket and comment it tags the language, reads the ticket’s advisor field, and marks the ticket eligible for an automatic reply only when no advisor is assigned. Then it picks one category from the mapping document, judging by intent, and writes it into two Zendesk fields. It never leaves notes or changes anything else.
  • Drafting agent. Its only output is a draft reply with Approve and Reject buttons. It assumes a macro exists, lists the library, searches by intent, situation and brand, and reads every candidate in full before choosing. smava macros for smava tickets, FC macros for Finanzcheck, the body used word for word. If nothing fits it has three exits in order: refer a disbursed loan to the partner bank, ask for clarification, or send the interim notice. It may not claim to have searched unless it did, and may never say it does not know or that a human will step in.
  • Two reply agents, one per brand. For eligible tickets they prepare one customer-ready reply and nothing else. Gender-neutral greeting with the customer’s full name, never Herr or Frau. Always “wir”, never “ich”. No signature, because Zendesk adds one. No link to check24 or verivox. No promise that the team will check, forward or arrange anything, and no claim to have attached a document. Every reply ends with one of four fixed closing sentences. A message in any language other than German or English gets the standard reply asking the customer to write in one of those two.
  • People stay in control. An agent changes a draft by writing @eesel in an internal note, and eesel reruns the whole macro search before it redrafts. A ticket with attachments goes to a person with a note instead of a draft.

A month of work

Between 8 August and 8 September 2026 eesel handled about 27,000 Zendesk tickets for smava and Finanzcheck, between 5,700 and 6,800 in each full week. The categorisation agent ran on about 14,600 of them and set about 23,000 tags. eesel prepared about 15,300 draft replies, ran about 14,400 searches across the macros and help center, and left about 800 internal notes.

The split shows where the work sits. The drafting agent, whose output waits for a person to approve, ran on about 12,200 tickets. The two reply agents, which only take tickets where the customer has no advisor, ran on about 1,100. Most of the month was eesel doing the sorting and the first draft, and a person doing the sending.

What is next

Tanja van Treel leads Customer Success at smava. The setup has one obvious dial: the share of tickets marked eligible for an automatic reply, decided today by a single field and covering about 1,100 of the 27,000. The categorisation, the macro search and the draft already run on their own, and every rule lives in the agents’ instructions, so changing what eesel may say is a text edit, not a project.

A month of work

What eesel did, from its own records

Every count on this page comes from eesel's activity log for smava, 8 Aug to 8 Sep 2026. The only estimate is the money and time saved, and the receipt shows how it is worked out.
$67,500
of people’s time a month, $810,000 a year
2,700 hours
about 68 working weeks, every month

$25 is an international benchmark for an hour of support time, not smava’s own cost.

Conversations handled, 8 Aug to 8 Sep 202626,999
×Minutes a person would spend on one6
=Hours of people’s time2,700
×Cost of an hour, all in$25
=A month$67,500
A year$810,000
Zendesk tickets and other live work
Live work per week, the last 13 weeks
06,72413,448Week of 15 Jun: 1,884Week of 22 Jun: 4,02322 JunWeek of 29 Jun: 1,503Week of 6 Jul: 4,4056 JulWeek of 13 Jul: 5,651Week of 20 Jul: 13,44820 JulWeek of 27 Jul: 6,691Week of 3 Aug: 6,9093 AugWeek of 10 Aug: 6,800Week of 17 Aug: 6,58617 AugWeek of 24 Aug: 5,754Week of 31 Aug: 6,21031 AugWeek of 7 Sept: 2,236
Show as a table
Week ofRuns
15 Jun1,884
22 Jun4,023
29 Jun1,503
6 Jul4,405
13 Jul5,651
20 Jul13,448
27 Jul6,691
3 Aug6,909
10 Aug6,800
17 Aug6,586
24 Aug5,754
31 Aug6,210
7 Sept2,236
When the work arrives
Hour of day, UTC. 13% of it lands between 10pm and 7am, when nobody is at a desk.
00:00 UTC: 7800:0001:00 UTC: 7502:00 UTC: 9103:00 UTC: 12504:00 UTC: 25505:00 UTC: 1,39006:00 UTC: 1,18406:0007:00 UTC: 2,14308:00 UTC: 2,43909:00 UTC: 2,68910:00 UTC: 2,27911:00 UTC: 2,17612:00 UTC: 1,92812:0013:00 UTC: 2,73214:00 UTC: 1,70615:00 UTC: 1,53116:00 UTC: 1,24917:00 UTC: 1,11818:00 UTC: 84918:0019:00 UTC: 55120:00 UTC: 46021:00 UTC: 29122:00 UTC: 17723:00 UTC: 87
Show as a table
Hour (UTC)Runs
00:0078
01:0075
02:0091
03:00125
04:00255
05:001,390
06:001,184
07:002,143
08:002,439
09:002,689
10:002,279
11:002,176
12:001,928
13:002,732
14:001,706
15:001,531
16:001,249
17:001,118
18:00849
19:00551
20:00460
21:00291
22:00177
23:0087
What it did
Actions taken in the customer's tools, last 30 days
Tickets taggedTickets tagged: 23,24223,242Draft replies for the teamDraft replies for the team: 15,30715,307Knowledge searchesKnowledge searches: 14,38714,387Internal notesInternal notes: 794794Emails to the teamEmails to the team: 11
Show as a table
ActionCount
Tickets tagged23,242
Draft replies for the team15,307
Knowledge searches14,387
Internal notes794
Emails to the team1

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