For this interview Lauren Clark Hill, our Customer Success Manager, talked with Chantal Schweizer, Practice Director, Strategic Data Services at Pivotree. Chantal assists various clients in enhancing their product information to achieve effective UX and data management. With 18 years of experience in the product data management field, Chantal has expertise in crafting cross-platform information structures, ontologies, and testing navigation. She is also a past recipient and judge of the TBCL Practitioner of the Year award. Throughout their discussion, Lauren and Chantal delved into the significance of product information management (PIM), the influence of training, and the process of introducing data management tools to others.
LCH: Tell us a little about you and your career evolution.
CS: Like many, I got into taxonomy completely by accident. I studied art history, but jobs in the arts were scarce. I started my journey at Grainger as part of the resourcing team and later transitioned to the product data team. While working on their Product Information Management (PIM) team, gathering product data from suppliers and normalizing that data, I discovered that I liked organizing the chaos. I spent approximately eight years collaborating on their taxonomy, managing attributes, gathering data, and implementing governance processes.
Then I moved to Schneider Electric with responsibility for PIM administration in one of their divisions. This gave me insight into data from the manufacturers’ side of the house complementing my knowledge of the distributor data I had worked with at Grainger. After a few years, I moved into consulting. I worked at Ideosity for about a year on PIM implementations, but I was still focused on the taxonomy. With implementations, I noticed that the focus was on the technology rather than the data. I was continuously trying to make sure that taxonomy was still coming into play. You can have a great PIM, but if you don’t have a great taxonomy, it’s not going to work.
Following this I joined Earley Information Science. I started as a junior taxonomist and worked my way up to senior taxonomist lead in the eight years I was there. I did sales for a little bit and then became director of the taxonomy team. Then I joined Pivotree as Director of Strategic Data Services. In this role, I worked with product data from the manufacturers and distributors, with their point of view. This perspective really helped garner trust with our clients. This perspective lets you see how different companies set up their data and the way they govern it, and helps you understand how people interact with it.
LCH: I find this background interesting. My first master’s is in art history, specifically history of decorative arts. A friend of mine who also works in taxonomy has an MLIS and an MA in art history. I have a belief that one of the reasons taxonomists do so well is due to this strong liberal arts research background. It feels like something we don’t touch on but is running underneath what we do.
CS: An arts background provides insight into how people view the world. We are interpreting a methodology, bringing art and science together to make a taxonomy, beautiful but functional, that works for multiple people. You want to make sure that a taxonomy is balanced, that there is flow, and intuitiveness can come into play. How people intuitively shop for their products, how they look through a taxonomy to browse for something are part of this. It’s all part of making an effective taxonomy.
LCH: I often joke that sometimes when I’m working on a taxonomy, it’s very structured and other times the method is to let the spirit flow through the keyboard and make it work. I find it interesting how many people with similar backgrounds have accidentally fallen into taxonomy.
CS: I’ve met a lot of people with music backgrounds and artistic backgrounds, like English majors, in this field. Also, there are a lot of people with MLIS and library science backgrounds. I was a librarian throughout high school and in college so I love swapping stories with my fellow librarians.. We (taxonomists) have a lot of similarities, there are a lot of commonalities and traits we share like a love of books and board games.
LCH: Tell us a bit more about Pivotree, the company and the work you do.
CS: I lead and guide a team of wonderful taxonomists who understand great product taxonomy and its best practices. Pivotree is big both in the technical space and the data space. They offer a road to frictionless commerce customer experience for our clients. Our systems enable manufacturers, retailers, and distributors to help their customers by streamlining the supply chain, data and eCommerce systems. Our team’s role is to make sure the data [and schema] is correct within these systems.
My team specifically works in this product data space. We make sure the data is successfully set up in a PIM or MDM system and ensure it translates through to the different eCommerce systems ready for customers and retail platforms. We make sure customers have all the data they need to quickly find their products and make a confident purchasing decision.
LCH: Can you explain what PIM systems are? How are they similar and different from taxonomies?
CS: PIM stands for product information management system. They are used as a central repository of the attributes you’re going to use to describe your products. The attribution taxonomy is the backbone of a PIM system. If you have a light bulb, your specifications are color, temperature, voltage, wattage. If it’s a ladder you have attributes such as maximum expandable height, material and weight capacity. These are technical aspects of the PIM that help you manage that data, ensure data consistency and data quality.
Then there’s the taxonomy side of it to consider. Taxonomy and the data can be looked at as a secondary thought in some PIMs but it’s a vital part of any PIM system. If you have a really great motor, but you’re running old, gunky motor oil through it then it’s not going to work as efficiently as it should. It works the same way for data in a PIM.
”If you have a really great motor, but you're running old, gunky motor oil through it then it’s not going to work as efficiently as it should. It works the same for data in a PIM.
Robust governance is necessary to ensure the data is managed efficiently. You need people who appreciate and manage the taxonomy and attributes. Having strong governance in place helps with this. Your data has to be clean, complete, concise and clear. If you don’t have these in place, then the PIM is not going to be as accessible as it could be. Make sure the health of your data is considered when you’re introducing a PIM system.
LCH: How was the transition from individual taxonomist to being team leader in the taxonomy sphere?
CS: I miss diving into a system and building a taxonomy. There’s something therapeutic when organizing the chaos. I don’t get the opportunity to do this as much as I used to. What I do love about my current role is being able to share knowledge and networking. I post videos on LinkedIn related to best practices. I have a series via LinkedIn called the Data Cafe where we talk to various people, clients, partners and professionals about product data.
My passion is to teach people about taxonomy. I have people reach out to me on LinkedIn asking for advice. Having the opportunity to talk taxonomy and finding other ways to help people advance their career, both internally with my team and externally with LinkedIn queries, means a lot.
LCH: What makes a good taxonomist? What do you look for when adding people to your team?
CS: There can be slight differences between external consultants and internal organizations but a few things remain the same. You want people who enjoy organizing, are detail oriented, and understand classification. They need to be able to work towards completion and be well versed in different types of taxonomies; be able to view the condition of the taxonomy, identify what’s broken and see the solutions. Additionally, they need to be able to understand working in a spreadsheet but have the knowledge of the other tools available.
In addition to these skills, as a consultant, you need strong client-facing skills. Taxonomists need to feel confident talking with clients, presenting taxonomies, and managing feedback. You may be required to work with a taxonomy that has been used for several years. It may not be fit for purpose and we need to socialize best practice to the client to gain adoption to our new taxonomy. Our role is to create a taxonomy that makes the client’s life easier. We all know change can be a challenge. People like to stick with what they are used to. This is where relationship skills are necessary. You need to be mindful, and able to direct them to a happy path to a new taxonomy.
Flexibility is part of this. You need to be able to identify potential problems and accept that if they don’t want to bend you have to present the risks and work with them to find an agreed upon path forward, even if that means bending best practice to allow them to walk before they run. There are always exceptions to every rule in the taxonomy best practice space. Be prepared to take them down a particular road and see where it takes us. Be prepared to fix roadblocks if necessary. Having that adaptability is very beneficial for a consultant. Being able to speak to the reason why we design the way we do and why it will help our client in the long run.
”Be prepared to take them down a particular road and see where it takes us. Be prepared to fix roadblocks if necessary.
LCH: What advice do you give to others when they are building a taxonomy project?
CS: This is a question I am asked a lot particularly from those who want to get into the taxonomy space. First, make sure you know the best practices. There are lots of resources available, great books like the Accidental Taxonomist and Taxonomies.
There are also great events, including face-to-face like KMWorld and the virtual Taxonomy Boot Camp London. There is also a great Discord channel called Taxonomy Talk. This is an excellent resource for bouncing ideas off of other taxonomists. There are opportunities to talk about conferences, learn about job opportunities, and explore new technologies that are available and emerging.
There are also a group of people I follow on LinkedIn who are evangelists and active networkers; like Jason Hein, Scott Taylor, Susan Walsh. There’s a lot of really great folks out there.
Looking at examples of good taxonomy, another helpful space is Baymard. A good space for taxonomy best practices. It’s a resource to see taxonomies, good and bad, different taxonomy levels, the facets, the attributes. There are useful avenues to learn about taxonomy, and to learn about private taxonomy specifically.
LCH: Governance is not really as complicated and scary as a lot of people seem to think it is.
CS: It really isn’t. You want to cultivate a governance culture but start small and work your way up. There are several important factors related to a process map, onboarding, attributes, modifying, audits and testing of the taxonomy, attributes and associated data. Consider all the roles that are needed and reflect on who is responsible. Who needs to be consulted and informed? Who are the owners of the different aspects of your data, who participates in those different aspects?
What are the steps for each process? Where’s the data coming from and where is it going to and making sure that you know who is responsible for each of those steps. Too many companies don’t have governance in place, and this makes data chaotic. Once you have these processes in place you need to make sure that data stays consistent over time. Style guidelines help you organize your formatting rules, capitalization, pluralization, special characters, and preferred terms.
You can have a governance council, a governance charter, or reporting meetings. There are a number of different things you introduce but start with that bare minimum and work your way up to those more robust governance programs. From the beginning, make sure you just know who’s in charge of what and what your processes look like.
LCH: I’m on a mission to evangelize on behalf of governance. It isn’t scary and style guidelines are important. It’s an issue I am speaking about at the next KMWorld event.
CS: George Firican is a great leader on this subject. You can read some interesting posts on his LinkedIn Channel on this subject.
LCH: What makes a good enterprise software? What are you looking for?
CS: When I’m recommending this to clients, what you look for in the software depends on the size and complexity of the data for that client. They may need flexibility to move data quickly. They may need to update data quickly, season to season, or manage different trends and keywords that are continuously changing in their world. There’s a lot of flexibility and speed of process needed.
For an industrial supply client, perhaps one who sells 1000s of actuators, they’re going to have a static product set – a robust attribute set with a lot more data to describe that product because it’s being used in technical applications. The item onboarding process is going to be a lot slower. Their needs are foundational, and they will have to handle big business rules. You need to consider the different ontological factors of it – product data, customer data, personalization and opportunities. Clients want to offer personal recommendations as well as access to customer order history or suggestions based on locality. Having that ontological set up will vary between different companies. We consider these different aspects when sourcing software for a customer.
LCH: You were recently awarded TBCL Taxonomy Practitioner of the Year – what was the project that led to that win?
CS: The award win related to a series of videos I made called The TaxoMOMinist. I created these videos in a previous role. I wanted to explain taxonomy best practice in simple terms with the help of one of my children, a teenager, to understand my work. He asked some great questions, and we would talk through examples: what was working and not working in a specific taxonomy. Unfortunately, they are not available anymore. I plan to revisit them in the future.
I was nominated for the Award by a former colleague. A lot of people watched the videos. They were being used as training tools. It was something simple but had a major impact. I am proud of winning, there aren’t many awards in the taxonomy sector. I have also been involved in judging future awards and it led me to further opportunities to speak at events.
LCH: What do you see as the positives and the challenges for industry?
CS: For positives, I would like to see expanded taxonomy testing. I’m hoping to find ways for an automated process to continuously test over time. Look at trends. Make sure you have dashboards in place that speak to the ROI of having strong data. This will give the ability to visually show how the data fill and accuracy rates go up and how they correlate with your conversion rates. What are your taxonomy success rates? Are you able to measure all of the different metrics over time to show that you have strong taxonomy and strong data? User adoption is going to continue to grow your sales and contribute to continuous revenue. This type of data success criteria is something I would love to see.
There is a big challenge in shifting people to move from taxonomies to ontologies. Ontologies help you connect taxonomies together and help with personalization and how to predict trends. I want to shift people from a taxonomy to an ontology mindset because of the benefits. We need to move away from spreadsheets to software like the products Synaptica offers. These tools are functional, efficient, and provide visual perspective. It’s hard to be visual in a spreadsheet when it comes to taxonomy. Improving the way, you present your taxonomy through the use of knowledge graphs, different metrics and measurables is effective and important.
Everybody wants a magic tool to create AI functionalities for them, but they don’t consider the importance of the data behind the scenes. A strong data set – clean organized data is necessary before any of these applications work. People don’t completely understand what’s available and how they can be used.
LCH: You talked about taxonomies and ontologies. Why is there the risk of reluctance? What is the barrier for making people embrace ontologies?
CS: It’s perceived as an additional layer of complication but overall, it makes life so much easier. Yes, there are multiple taxonomies, but if you can enable different taxonomies to link and talk to each other there’s so many important data analytics that you can access. You can access data and learn about your customers and different sales patterns. If you can find different data sets to help inform your choices, these can lead to big changes in how you operate. Understanding your customers, their personas, their buying patterns, plus understanding your product data, supply chain, distribution makes a big difference. This adds to the success of any business and takes it beyond return on investment.
Synaptica Insights is our popular series of use cases sharing stories, news, and learning from our customers, partners, influencers, and colleagues. You can review the full list of Insight interviews online.
