Clienteling
What the team getsA record of commitments and messages to personalise.
Define whom to contact, when and why. Prepare the context and draft messages, then let the advisor personalise the relationship.
Explore the clienteling use caseChiara, our AI sales coach for retail
What the team getsPractice scenarios and focused coaching feedback.
Advisors practise greetings, objections and brand storytelling out loud. We adapt the scenarios to the retailer and help managers continue the coaching.
Explore the Chiara use caseCS Automation
What the team getsPotential to free up around 30% of customer service time, subject to pilot validation.
An e-commerce brand wants to support strong growth and seasonal peaks. We propose automating returns, order changes and parcel enquiries through to resolution.
Explore the CS automation use caseClauzy, our AI assistant for an agency network
What the team getsFiles and documents prepared for the agreed assignments.
The advisor makes a request by phone or email: a price study, viewing preparation or follow-up on a file. We adapt assignments to the network’s standards, tools and approval requirements.
Explore the Clauzy use caseField prospecting
What the team getsA route plan, visit briefs and action tracking.
Identify the accounts to visit, plan the route and prepare the information needed at each stop. Then organise the next steps from the salesperson’s debrief.
Explore the B2B prospecting use caseKnowledge base and AI assistance
What the team getsAn answer with a source, or a point to confirm.
Help advisors find information about a piece, its care or a service. Prepare answers from documents approved by the retailer.
Explore the product knowledge use caseRetail operations
What the team getsA schedule, named owners and approvals to track.
Prepare tasks, deadlines and approvals from a brief. Give managers a view of the work to do and the issues to resolve.
Explore the retail operations use caseDirect selling
Orders ready for reviewThe consultant reviews the summary; the order management team tracks each order through to invoicing.
After the party, the consultant sends a voice note or photos of the order forms. The AI agent prepares the orders in the brand’s system, checks product codes and applicable offers, and flags missing details.
Explore the direct selling use caseAdvisors need to retrieve shared preferences, prepare the next meeting and keep their commitments. Information may sit across tools and personal notes. Managers want to track actions while allowing advisors to maintain individual relationships with clients.
We define a clienteling playbook with the team: reasons to contact clients, useful information and follow-up rules. We then automate preparation of contact lists, meeting briefs and draft messages within the agreed scope. The advisor checks the context, personalises the message and decides whether to send it.
The advisor can find the meeting context, open commitments and next actions. They have a draft message linked to a specific reason for contact.
An illustration of client follow-up, without real personal data.
Review the customer journey, reasons for contact and available information; define follow-up rules.
A clienteling playbook and a list of required data.
Work with advisors and managers on debriefing, message personalisation and client allocation.
Follow-up routines and shared usage guidelines.
Build meeting preparation, debrief summaries and draft messages using the authorised context.
Meeting briefs and a record of commitments to review.
Maintain access, correct information and adjust rules based on team feedback.
Quality monitoring and updates to the playbook.
Preparation time, commitments handled on time and the share of draft messages usable without major rework. Tracking replies and visits depends on the data and timeframe agreed.
Authorised data, contact rules, access and responsibilities. We can work with an existing CRM or define a client memory limited to the agreed need. A clienteling assignment does not require replacing your CRM.
Advisors know the training materials but need to find their words in front of a client. Greetings, price objections and cross-selling take practice. Managers need specific situations to revisit with their teams.
Chiara is the AI sales coach we developed for retail. Advisors practise out loud with a simulated client, ask the coach for help and revisit part of the conversation. We prepare scenarios using the retailer’s products, brand story and service standards.
The advisor has a scenario to replay and a coaching point to work on. The manager has guidelines and exercises to continue the work with the team.
An example session, with no recording of a conversation with a real client.
Choose the sales situations to practise with leaders and managers; review the materials and service criteria.
Priority scenarios and coaching guidelines.
Prepare a workshop with advisors, explain the feedback and arrange further practice with the manager.
An in-person workshop and practice programme.
Adapt the simulated clients, brand content and coaching; test their relevance with the team.
Voice-based practice configured for the retailer.
Maintain the service, update the content and adjust scenarios based on feedback.
Service monitoring and updated exercises.
Use and repeat practice, the relevance of coaching and feedback from managers. Depending on the project, we also agree on in-store observations and sales indicators, with a baseline defined at the outset.
Scenarios, products, languages and access channels. Advisors work on simulated conversations; we do not ask them to record their clients. We define which information managers can access and which stays in private feedback.
An e-commerce brand aims to nearly double its business, according to the ambition shared during discovery. The team wants to handle growth and seasonal peaks while keeping time to advise customers. Today, staff move between the helpdesk, online store, logistics portal and carriers. An order change requires updates in several tools; a lost parcel means days of follow-ups.
We propose using AI agents to handle requests from order checks through to resolution: check parcel status, open a carrier investigation, follow up, gather supporting documents and keep the customer informed. For returns and order changes, we agree authorised actions and approval rules with the team.
The ambition is to expand autonomy, one workflow at a time, to the cases that consume the most staff time. We assess connections to existing tools and browser access to the logistics portal. The team keeps advisory conversations and takes over exceptions that require human judgement.
The team estimates that automation could free up around 30% of its time. The aim is to handle more requests, reduce reliance on seasonal staff and spend more time advising customers by phone. The team’s preliminary estimate during a discovery discussion, to be validated through an audit and pilot. No measured gain is claimed at this stage.
Review cases with the team, map actions across tools and measure staff time spent on each type of request.
Workflow map, time baseline and automation priorities.
Define delegated actions, approval thresholds and exceptions; prepare the team to supervise agents and take over a case.
Autonomy rules and a human handover process.
Build an initial complete workflow, connect authorised tools and test actions on representative cases before the pilot.
Pilot agent, action log and exception tests.
Compare staff time before and after, check resolution quality and expand workflows based on pilot results.
Tracking of hours freed up, cost per resolution and an expansion roadmap.
We measure human working time per case, including follow-ups and rework, then hours freed up at a comparable volume. We also track response time, complete resolution, errors and cost per case. Automated ticket volume alone is insufficient: complex cases can account for most of the work.
Access to the helpdesk, online store, logistics provider and carriers; rules for returns, replacements and order changes. We test the feasibility of each connection and agree approvals before any action. This case describes a deployment ambition, with gains to measure in a pilot.
Between appointments, advisors need to prepare files, find information, write documents and follow up. Across a network, they also need to respect agency-specific practices, permissions and approvals.
Clauzy is the AI assistant we developed for a network of real estate agencies. Advisors make requests by phone or email. Depending on the assignment, they receive a price study, prospecting preparation, a listing or follow-up messages to review. They can also request that a viewing acknowledgement be sent for signature and that the signed document be returned.
We adapt this foundation to the assignments and standards agreed with the network.
The advisor receives the document they requested, along with the points to check. They can resume the client relationship with a prepared file and a record of the next steps.
An illustration of a Clauzy assignment. No valuation result or real client data appears here.
Review files and tasks with advisors; select priority assignments and the network’s requirements.
Assignment scope and document acceptance criteria.
Support pilot agencies with their first requests and the checks to carry out; gather feedback on difficulties.
An onboarding programme and follow-up sessions with agencies.
Configure documents, sources and rules; adapt assignments and authorised connections.
Real estate assignments adapted to the network’s practices.
Monitor deliveries, correct incidents and outputs, maintain connections and develop support for further requests.
An operated service and monitoring of delivery quality.
Delivery time and cost, the share of documents accepted without rework, the work left to the advisor and repeat use. We agree the criteria with the network before expanding the scope.
Document templates, priority assignments and access rules. CRM connections, notifications and actions involving third parties depend on the authorised scope. The advisor checks business content; actions such as signature requests follow the agreed approvals.
The salesperson prepares visits from account lists, confirmed appointments and scattered information. They need to choose which businesses to meet, plan travel and arrive with a specific reason for each visit. After the round, they need to review the conversations and prepare follow-up.
We define priority criteria, territory and route constraints. We automate preparation of the visit plan and account briefs using authorised information. The salesperson checks the suggestions, confirms appointments and debriefs after visits to prepare next actions.
The salesperson has an order of visits, information on contacts and an objective for each stop. On returning, they can review commitments and next steps account by account.
An illustrative route plan with fictional accounts. Times, availability and travel still need checking against the project’s sources.
Review visit preparation, targeting criteria, territory and available sources.
Priority rules and the information required to plan a round.
Agree with salespeople how to validate the route, prepare conversations and debrief after each visit.
A routine for preparing and following up on visits.
Gather account information, prepare the order of visits within the constraints and structure the follow-up from each debrief.
A route plan, account briefs and next steps.
Update sources, correct data and adjust rules based on completed rounds.
Ongoing preparation support and tracking of discrepancies found in the field.
Preparation time, information reliability, travel and visits completed against the plan. We also track agreed next actions and sales follow-up within the timeframe and data scope agreed.
Target accounts, priority criteria, mapping sources and access to calendars or the CRM. The salesperson retains control over visits and contact. We do not promise the shortest route or guaranteed appointments.
An advisor needs information about a material, care instructions or service conditions. They have to find the right document and check that it is current. Launches and collection changes add to the content they need to know.
We organise a knowledge base from documents approved by the retailer and provide access through questions. The AI assistance must cite its source, use the agreed version and flag anything the documentation cannot confirm. This knowledge base can also support briefings and practice exercises.
The advisor has an answer linked to reference documentation. They can identify points that need confirmation before making a commitment to the client.
A fictional example showing how to handle missing information, not an answer about a real product.
Review advisors’ questions, the available documents and who approves them.
A defined set of reference documents and priority questions.
Define who publishes and updates content and who handles unanswered questions; prepare advisors to check sources.
A process for updating content and guidelines for use.
Organise the content and build search and sourced answers; test missing or conflicting information.
A searchable knowledge base and assistance tested against your questions.
Update documents, remove outdated versions and correct reported answers.
A maintained knowledge base and tracking of unresolved questions.
Search time, the share of answers accepted without correction, relevant source references and the handling of unanswered questions.
Reference content, access rights and updates. Live stock, prices or availability require a connection to the relevant source; a document library alone is not enough.
A launch, window change or private presentation requires coordination between stores, the network and central teams. The manager needs to know who prepares what, by when and with whose approval.
We define the sequence and responsibilities, then put retail operations assistance in place. From an approved brief, we automate preparation of the schedule, task allocation under agreed rules and approval tracking. The manager confirms assignments and changes.
The manager has a schedule linking tasks to owners and required approvals. They can see which points to review with the teams before the event.
An example of coordination, with responsibilities to adapt to your organisation.
Reconstruct a launch or event, identify dependencies and clarify the decisions required.
Processes, responsibilities and approval points.
Agree with the teams how to share a brief, report a delay and approve a change.
A shared way of working and an initial test event.
Build schedule preparation, task lists and authorised reminders from the briefs.
An operational schedule and approval tracking.
Track incidents, maintain connections and update rules as the organisation changes.
A maintained process and adjustments after each event.
Time spent coordinating, tasks completed by the deadline, pending approvals and revisions to the schedule.
Roles, approval rules and tool connections. Managers retain responsibility for staffing decisions, trade-offs and operational approval.
The party is over, but the consultant still has orders to enter. They go through the forms, look up product codes, check promotions and work out the host’s rewards. If a customer has left out a size or an address, the consultant has to get back in touch before finishing.
At head office, the order management team takes over. Staff update the ERP, check payments and prepare invoices. Information is spread across the consultant’s messages, their ordering portal and the company’s business systems. To answer a customer or resolve a hold-up, the team has to find the latest exchange and check what has already been done.
The consultant sends photos of the order forms and can add a voice note with further details. The agent matches the products to the catalogue and prepares the orders in the brand’s system. It checks stock and prices, applies the offers valid on the sale date and calculates host rewards using the brand’s rules.
It asks the consultant for any missing details and submits the orders for review. An unclear product code or an amount to confirm appears beside the relevant line in the order summary.
Once the order is approved, the agent updates the relevant systems and tracks it through to invoicing. It checks delivery progress and payment status, prepares the invoice under the brand’s billing rules and flags orders that need the team’s attention. For sales that start with a quote, it uses the accepted quote to prepare the order.
The consultant checks the items, quantities and order totals without entering everything again. They can see which questions to ask customers and which choices need confirmation.
The order management team can see where each order stands: awaiting approval or payment, partly delivered or ready to invoice. Staff have the documents and correspondence they need to take over.
We follow orders with consultants and the order management team, from the party through to payment. We identify duplicate entries, repeated checks and causes of delay.
The tasks to automate, the rules to apply and the systems to connect.
We help consultants learn how to submit requests and review orders. With the order management team, we agree who answers questions and who approves changes.
Working procedures for consultants and the order management team.
We connect the systems and test order processing with a pilot network, including incomplete forms, stock shortages and conditional offers.
An agent configured for the network’s orders.
We review corrections with the team and adjust the process as catalogues, offers and software change.
Tracking of turnaround times and errors, with the changes needed to address them.
We compare the time spent on orders before and during the pilot, including data entry, checks and corrections. We track the time from the party to order approval and the proportion of orders that need rework.
For the order management team, we measure the time spent finding information and following up on outstanding items, as well as whether invoices are issued on schedule.
With your team, we choose the steps to cover and the systems to connect: the consultant portal, ERP, invoicing and payment tracking.
The consultant or order management team approves each order before it is finalised and each payment request before it is sent. They decide how to handle uncertain amounts, unavailable products, disputes and exceptions to the reward rules.
Describe a situation your team wants to improve. We will review your working practices, the changes to support and the automation or AI that could help. We will agree the deliverables and success criteria with you.