Imagine a company invited to participate in a major tender. Within a short timeframe, it needs to review a lengthy tender specification, compare it with technical documentation, references, sales presentations and materials used in previous projects, identify the requirements, determine what information is missing, prepare a consistent proposal and adapt its language to the target market and customer. The challenge is not simply the time required to read and write. The real risk is overlooking a requirement, using an outdated document, presenting inconsistent information or failing to highlight relevant company experience that could make a difference in the final evaluation.
This is precisely where Generative Artificial Intelligence can become far more valuable than a simple chatbot used to answer occasional questions. Tools such as ChatGPT Projects, Claude Projects and Gemini Gems allow companies to create dedicated workspaces where instructions, reference materials and corporate knowledge can be brought together, ensuring greater continuity from one task to the next.
The same approach can be adopted by a company seeking to enter a new market, strengthen its lead generation activities, improve its international e-commerce operations or increase its effectiveness on a marketplace. In all these scenarios, information is scattered across catalogues, price lists, presentations, product sheets, campaign reports, sales data, benchmarks, competitor analyses and internal documents. At the same time, business decisions require a comprehensive understanding of different sources and continuous comparison between alternative strategies.
ChatGPT and Claude Projects: How to Create a Shared Workspace
Creating a Project in ChatGPT or Claude, or a Gem in Gemini, means establishing a consistent working environment in which the chatbot can operate more effectively. It understands the role it is expected to perform, the company's objectives, the examples it should use as references and the specific instructions governing how it should interpret sources and present its analyses.
The quality of this environment depends primarily on the initial instructions. These should clearly define the role the chatbot must assume, how it should handle the documents and sources available to it, and the perspective it should adopt when responding to subsequent requests.
For example, a B2B manufacturing company looking to expand into Germany could instruct the system to act as a senior digital export consultant with expertise in industrial markets and lead generation. A company selling directly to consumers online, on the other hand, could define a role more closely aligned with that of an e-commerce manager specialising in UX, Conversion Rate Optimisation (CRO), advertising and digital merchandising.
Defining the style of responses is equally important. A project designed to support strategic decisions should produce clear analyses, distinguish facts from assumptions, highlight information that is insufficiently supported by evidence and identify the additional data needed to reach more reliable conclusions.
The chatbot can also receive specific instructions regarding tone of voice, level of detail, response format and the need to avoid unsupported claims.
These instructions become even more effective when the project includes company materials to use as references. A collection of high-quality product descriptions, sales presentations, case studies, FAQs, catalogues, landing pages and marketing materials enables the model to better understand the company's communication style and the structure of its existing content.
For an international e-commerce business, selected high-performing product pages can be uploaded so that the chatbot can identify their common characteristics, level of detail, tone of voice and information hierarchy. In a B2B environment, companies can use sales presentations, success stories and materials developed for international distributors or buyers.
Rather than simply copying these examples, the system should use them as reference points to ensure that new content remains consistent with the company's positioning.
This is particularly important for digital export activities, where effective international communication often depends on maintaining a consistent brand identity while adapting messages, content and arguments to the characteristics of individual markets, channels and target audiences.
Generative AI for Market Analysis, Scenario Planning and Internationalisation Decisions
Once this context has been established, Projects and Gems can support a wide range of activities, becoming particularly useful when exploring new international markets.
Through the Deep Research capabilities available in leading AI chatbots, a company can ask its dedicated project to develop alternative market-entry scenarios for France, Germany or the United States. It can then compare different approaches, such as direct e-commerce, marketplace sales, local distribution or digital lead generation.
The chatbot can help identify the variables to consider, create comparison matrices, highlight missing data and recommend areas requiring further investigation.
The value lies not in obtaining an immediate answer to the question of which market to enter, but in improving the decision-making process and breaking down a broad strategic challenge into a sequence of more manageable analyses.
Chain-of-thought prompting techniques encourage users to request not simply an answer, but a structured approach to reaching it, allowing the analysis to develop progressively through an interactive conversation.
Research activities can begin with the company's existing information and then be enriched with market data, competitor websites, industry reports, search engine results page (SERP) analyses, marketplaces and other publicly accessible online sources.
By progressively expanding the available reference material, the chatbot can help develop a more comprehensive understanding of the competitive landscape and assess whether the company's initial assumptions are supported by evidence.
These workspaces are also valuable when a company has already developed a strategy and wants to challenge it before committing resources.
The chatbot can act as a strategic sparring partner, evaluating a project from the perspective of a sales director, marketing manager, international buyer or local distributor. It can then switch perspectives and act as a devil's advocate, identifying weaknesses in the proposed initiative and suggesting tests to validate key assumptions before launch.
For example, a company planning to introduce a new product on a marketplace can ask which factors might limit its visibility or conversion performance. It can compare its offering with competitors and assess whether pricing, customer reviews, image quality or product page structure could represent potential obstacles.
A B2B company can adopt the same approach to evaluate a LinkedIn campaign, a landing page or a commercial proposal targeting international distributors and importers.
The ability to simulate different perspectives is particularly valuable in internationalisation decisions. One of the main risks of entering a new market is evaluating the opportunity exclusively from the company's own viewpoint.
Customers, buyers, distributors and business partners may assign very different levels of importance to pricing, brand awareness, after-sales support, certifications, delivery times and commercial terms.
AI Projects for Online Sales
Projects and Gems also become particularly useful when analysing marketing campaign data.
A chatbot can process tables and reports, identify anomalies, connect different performance indicators and suggest potential explanations to investigate.
For example, an increase in traffic to an online store from Germany combined with a decline in conversion rate could indicate a targeting issue, a mismatch between advertising messages and landing page content, friction in the purchasing process, or concerns relating to pricing, shipping or brand trust.
Artificial Intelligence can therefore also support User Experience (UX) and Conversion Rate Optimisation (CRO) activities by helping identify obstacles that prevent users from completing a desired action.
In an e-commerce environment, it can analyse the structure of a product page, assess the clarity of the information provided, compare content hierarchy with that of competitors and suggest potential A/B tests.
For a lead generation website, it can evaluate the effectiveness of the value proposition, the presence of trust signals, the quality of calls to action and the amount of information requested through contact forms.
The same approach applies to marketplaces, where customer behaviour is influenced by a combination of visibility, pricing, reputation, image quality, product listing completeness and the ability to differentiate an offering within a highly competitive environment.
A chatbot can help compare competing product listings, identify recurring characteristics among better-positioned offers and suggest which elements of product presentation should be tested.
A dedicated project can also serve as a central workspace for continuously monitoring advertising campaign and lead generation performance.
Data can be interpreted in the context of the company's objectives, business priorities and historical performance.
The value increases when the chatbot goes beyond describing past results and instead develops hypotheses, recommends further checks and connects performance indicators with potential operational decisions.
Ultimately, the same environment can be used to prepare tenders, develop commercial proposals, analyse new markets, interpret campaign performance and explore new growth opportunities.
By maintaining a richer context and drawing on relevant reference materials, the chatbot reduces the need to start from scratch each time a new task arises.
Projects and Gems can also be shared among colleagues, allowing different team members to work from the same background information and instructions while conducting separate conversations tailored to their individual responsibilities and objectives.
For companies involved in digital export, international e-commerce, marketplaces and B2B lead generation, the most significant opportunity is therefore to move beyond occasional AI usage and develop specialised workspaces where information, examples, instructions and evaluation criteria can be applied consistently over time.
“Use AI not simply to work faster, but to work better.”
The main advantage is not the speed at which a chatbot can generate content or produce a summary. Its greatest value emerges when AI helps businesses interpret complex information, challenge existing assumptions, compare alternative scenarios, analyse data and make better-informed decisions.
Projects and Gems consequently become less like simple content-generation tools and increasingly resemble collaborative workspaces where companies can organise knowledge, conduct analyses and evaluate different perspectives as they navigate new markets and increasingly complex business decisions.