{"id":46454,"date":"2026-02-03T11:57:24","date_gmt":"2026-02-03T10:57:24","guid":{"rendered":"https:\/\/implema.se\/kundreferenser\/how-nelson-garden-improves-its-retailers-experience-with-ai\/"},"modified":"2026-02-03T14:02:27","modified_gmt":"2026-02-03T13:02:27","slug":"how-nelson-garden-improves-its-retailers-experience-with-ai","status":"publish","type":"kundreferenser","link":"https:\/\/implema.se\/en\/client-cases\/how-nelson-garden-improves-its-retailers-experience-with-ai\/","title":{"rendered":"How Nelson Garden improves its retailers’ experience with AI"},"content":{"rendered":"\n

AI can still feel abstract to many. But for Nelson Garden, it is about something very concrete: making everyday life easier for its retailers \u2013 and smarter for its own business. <\/strong><\/p>\n\n

<\/p>\n\n

Growing order pressure became the starting point for the AI journey<\/strong><\/strong><\/h3>\n\n

Nelson Garden is one of the Nordic region’s leading players in the garden trade. For over 90 years, the company has worked to make cultivation accessible to more people, professionals and hobby growers alike. Behind seed packets, bulbs and garden tools lies \u2013 just like in all retail companies \u2013 an extensive machinery that handles thousands of orders, logistics, seasonal peaks and customer service matters. <\/p>\n\n

Each year, Nelson Garden receives tens of thousands of orders from its retailers, many of them sent as PDFs via email. These were previously registered completely manually, a time-consuming job that easily led to stress and errors, especially during peak season when order volume often exceeded available capacity. <\/p>\n\n

\u2013 We noticed that we couldn’t keep up. In addition to our deliveries being late, the stress meant that the wrong goods were sometimes sent <\/em>, says Martin Borgstr\u00f6m, CEO of Nelson Garden.<\/p>\n\n

The decision to invest in AI grew out of a concrete need: the pressure in order reception could no longer be handled with manual capacity. Something needed to be done \u2013 and quickly. <\/p>\n\n

Nelson Garden had been curious about AI for some time, but wanted to find a context where the technology could quickly create concrete business benefits. Here they had found one. <\/p>\n\n

<\/p>\n\n

Automated order management \u2013 without changing the way of working<\/strong><\/h3>\n\n

Nelson Garden has long been a customer of Implema, where Implema is their SAP partner. When it was time to solve the challenges in the order flow, they turned to their partner and presented their thoughts. <\/p>\n\n

\u2013 We didn’t want to start a big AI project. We wanted to solve a real problem \u2013 quickly and efficiently \u2013 without changing how our retailers work <\/em>, says Martin Borgstr\u00f6m.Implema suggested that they test Sally, a proprietary AI solution. Using AI and OCR technology, Sally reads and interprets the content from unstructured documents, such as PDFs, structures the information and then registers the order directly in the business system \u2013 completely without manual intervention. \u2013 Sally is developed to solve real problems in business flows. Not as a future project, but as a tool here and now. In Nelson Garden’s case, the need was clear, the volumes high and the effect measurable <\/em>, says Jesper Lindsten, integration and AI specialist at Implema.<\/p>\n\n

Everything \u2013 OCR reading, interpretation, formatting and registration in the business system \u2013 takes place “behind the scenes”, without disturbing the existing processes.<\/p>\n\n

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Great effects in a short time<\/strong><\/h3>\n\n

After a smooth implementation, Sally was up and running. Nelson Garden’s first AI project yielded results almost immediately: <\/p>\n\n

    \n
  • Over 80% of incoming PDF orders are now handled automatically<\/strong><\/li>\n\n\n\n
  • Shorter lead times<\/strong> \u2013 all orders are registered and processed the same day, even during peak season<\/li>\n\n\n\n
  • 70% fewer misregistrations<\/strong>, which has led to fewer complaints<\/li>\n\n\n\n
  • At least 1,200 hours have been saved in customer service <\/strong><\/li>\n\n\n\n
  • By freeing up time for customer service, staff have been given a more sustainable working environment<\/strong><\/li>\n\n\n\n
  • Better use of resources in warehouse and logistics<\/strong>, thanks to faster order flow<\/li>\n\n\n\n
  • Retailers get a better experience<\/strong>, without having to change their routines<\/li>\n<\/ul>\n\n

    With Sally, Nelson Garden has not only streamlined its internal processes, it has created a solution that strengthens support for retailers, without changing their way of working. The result is faster flows, fewer errors and a clearly improved working environment. \u2013 The best thing is that our retailers haven’t had to adapt at all. Everything happens in the background, but they naturally notice that deliveries work better and that the right goods arrive on time <\/em>, says CEO Martin Borgstr\u00f6m.<\/p>\n\n

    <\/p>\n\n

    Next step: AI that acts \u2013 not just assists<\/strong><\/h3>\n\n

    With Sally in place, Nelson Garden has taken a first, but important, step in its AI strategy. The technology is now being further developed to not only interpret orders, but also understand deviations and independently propose or implement measures. \u2013 We are moving from an assisting AI to an agent-like solution. Sally learns from previous cases, adjusts itself and takes initiatives. That makes the flows even smarter <\/em>, says Jesper Lindsten.<\/p>\n\n

    <\/p>\n\n

    Chatbots that answer around the clock<\/strong><\/h3>\n\n

    In parallel, Nelson Garden has introduced two AI-based chatbots. One is used for questions about cultivation, assortment and sales conditions and is aimed primarily at retailers and consumers. It is also used internally and then as a support for, among other things, customer service. <\/p>\n\n

    The second chatbot facilitates the handling of returns for retailers, a process that previously often involved both uncertainty and additional work. The aim is to create a simpler, smarter and more accessible support experience \u2013 regardless of the time of day. <\/p>\n\n

    Already in the first month, the return chatbot handled 265 conversations. The results are very promising: the answers have been both relevant and informative and several retailers have expressed appreciation for the concrete support in return issues. <\/p>\n\n

    At the same time, the chatbot provides valuable insight into retailers’ most common challenges. That knowledge becomes a basis for further improving the return process and making everyday life even easier for retailers in the future. <\/p>\n\n

    Strategy that grows with the business<\/strong><\/h3>\n\n

    As part of the next phase, Nelson Garden is also reviewing the technical infrastructure for AI. The focus is on how data is collected, stored and quality-assured, but also on how different AI solutions can be made available to the entire organization in a unified and structured way. <\/p>\n\n

    The goal is to build a stable and future-proof foundation where AI does not become individual point efforts, but a natural part of the business’s common toolbox.<\/p>\n\n

    Lars-Erik Od\u00e9n, independent consultant, has driven Nelson Garden’s AI initiative over the past year. He believes that the most important thing is to get started, not to wait for perfection. \u2013 We started small, learned a lot and have gradually developed our strategy. Today, we are running ambitious AI projects, including together with Linnaeus University, where we use AI to improve our sales forecasts <\/em>, he says.<\/p>\n\n

    He emphasizes that AI is not a goal in itself, but a tool to drive real business development and create business value:\u2013 When we use AI correctly, it helps us make better decisions, free up time and focus on what really makes a difference for our customers, our employees and our retailers<\/em>.<\/p>\n\n

    The entire business involved <\/h3>\n\n

    Nelson Garden has now started an AI council with employees. The purpose is both to create engagement and to get ideas on how they should use AI in the business. They have also conducted training at various levels, including a workshop with management, to inspire increased use and understanding of how AI can be a support for them. The next step is targeted training efforts for the organization’s leaders, with a focus on how leadership changes in line with increased AI use. In a more hybrid organization, where people and AI-based systems collaborate, issues such as responsibility, decision-making, trust and change management become even more central. The training aims to give managers practical tools to lead in this new reality. In parallel, Nelson Garden places great emphasis on educating the organization in and complying with the EU’s AI regulation. Through increased knowledge of the regulations, it is ensured that AI is used in a responsible, transparent and lawful manner, both for today’s solutions and when new ones are introduced in the future. Regulatory compliance is thus not seen as an obstacle, but as an enabler for long-term sustainable AI development. <\/p>\n\n

    “A concrete step that has already had a big impact”<\/strong><\/h3>\n\n

    Martin Borgstr\u00f6m summarizes:<\/p>\n\n

    \u2013 For us, AI is not just a way to become more efficient. We want to use the technology to strengthen our collaboration with retailers. By making better decisions together, based on data and insights, we can create a more relevant range, better timed campaigns and an easier everyday life in the store. With Sally, we took a concrete step that has already had a big impact. <\/em><\/p>\n\n

    <\/span>
    \n

    About Sally<\/strong>Sally is Implema’s proprietary AI solution for automating order management from unstructured documents, such as PDFs. Using AI and OCR technology, Sally interprets the content, structures the information, validates and registers the order directly in the business system \u2013 without manual intervention. Sally is:<\/p>\n\n\n\n

      \n
    • Fully integrable with SAP and Microsoft Dynamics<\/li>\n\n\n\n
    • Self-learning and adaptable. Continuously improved via feedback <\/li>\n\n\n\n
    • Robust and scalable \u2013 especially suitable for seasonal volume flows<\/li>\n\n\n\n
    • Transparent with clear logging and exception management<\/li>\n\n\n\n
    • Implementable without disturbing the customer’s or retailer’s way of working<\/li>\n\n\n\n
    • Created to provide rapid business benefits<\/li>\n<\/ul>\n<\/div><\/div>\n\n

      <\/p>\n\n

      <\/p>\n","protected":false},"excerpt":{"rendered":"

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