Even if a company doesn’t consider itself seasonal, things like interest & demand can still be affected by economic influxes & seasonality. We recently had a webinar hosted by our friends at Glasswing Ventures, which included a panel of cutomer service leaders from companies like Balsam Brands and Support Services Group on how seasonal businesses use Automation and AI to help with seasonality and scale. The talk touched on topics such as:
- How businesses currently using AI to achieve scale
- The most critical current benefit of AI deployment
- What's next for the future of AI and Automation
- How businesses are using automation to predict consumer and product demand
- Suggestions for companies who are exploring implementing AI to support their growing and seasonal businesses.
If you missed the talk, don't worry! Catch up on the full webinar below, watch the videos, read through the questions, and learn more about how businesses use AI to help with seasonality, onboarding, and predicting trends. Enjoy our talk, and we hope you will join us for our future discussions!
Rina Kremer- Is a Senior Customer Success Strategist and works on the Balsam Brands team. Rina primarily works in learning and development and knowledge management. Balsam Brands is a seasonal business specializing in artificial Christmas trees and the Christmas market and is also heavily involved in the sales of other home decors. The brand primarily serves the US market but is growing in Europe and Australia as well.
Shaun Mackinnon- Is Balsam Brands Program Manager at Support Services Group. Shaun, who works very closely with Balsam Brands, has been in the company as a support leader for 14 years.
Don't have time to watch the whole talk? We made it fast and easy for you to get to the information you're looking for the most because that's what Talla does! Just click a question below to learn more!
- Tell us about the specific challenges your company faces being seasonal?
- How are you using Talla to address some of the challenges of seasonality and scale?
- How does your team use Talla directly?
- What’s the most important benefit of the Talla deployment, and how has it impacted your role?
- Has Talla impacted your team members when it comes to training? Have you found it helpful?
- How are you measuring the success of Talla, are there particular metrics you look at to show it is having an impact?
- What suggestions would you give companies who are exploring implementing an AI knowledge-base system or other kinds of AI to support their business?
- What would you recommend that people do to make sure they are constantly improving the value they are getting from AI?
- What tips do you have for getting users to adopt a new piece of technology, and how do you make sure things are getting adopted?
- Are you using an external KB System? Where is Talla tapping into to deliver the right information to your agents?
- What are some of the new ways you might use AI, and what are some AI tools you are excited to work with in your business?
- Are you watching any trends or new technologies in the customer service and customer success spaces that you are thinking about bringing into your organization?
- Are you using any automation or analytics to predict changes in your demand or consumer interests?
- How easy or hard was it to implement Talla?
- What is your favorite feature of Talla?
Can you tell us a little bit about the specific challenges that your company faces being seasonal?
Rina Kremer: Everyone faces seasonality to some degree. We are kind of in a unique position because we sell Christmas-specific decor and artificial Christmas trees. We don't really have the rest of the year to rely on, should something go wrong during the season, if we have inventory shortages, or something is late, and especially we saw that last year a lot. Try as we might, we can't really push a bunch of customers to order a tree in February or March, it's just not going to happen. We don't have an evergreen product in the sense that you can just buy it after Christmas and still be happy to have it. So I think we, in particular, are in a tricky place where we really do rely so heavily on those last few months of the year to execute on all of our deliverables, scale more product in stock, and get that to our customers in a really tight timeline.
So I’d say all of our functions are really centered around those last few months of the year, whether that’s all your prep for us and getting ready for it, and then we're on 24 seven during the season, or for other functions like recruiting or accounting they kind of have to do everything before that time, and then they have to hit pause and support the rest of the business that way, so all those functions and of course customer service as well. Most of the year, we have several hundred agents because we're pretty slow, and then we onboard several hundred more where they only get about two weeks of the year to train, and then they’re with us for two to four months, and we do that every single year, so really all of us are kind of tied to that end of year deliverable.
How are you using Talla to address some of the challenges with seasonality and achieving scale?
Rina Kremer: We use Talla internally, so it's agent-facing for us, and I would say it's really crucial to get all the information to our agents at the time that they need it. They're only with us for so long.and while we do have agents that come back to us, things change all the time. It'll change midseason or it'll change right before the season, so we can't count too much on those first two weeks of training to really give them everything they need. It's not really fair to assume that they can just absorb all of it in two weeks, and then they are fine the rest of the year. So it's really important that we give all that information to them whenever they need it and make sure that it’s right at their fingertips, regardless of if they're here in the states with us or at one of our globally dispersed contact centers.
Does your team also use Talla directly? Can you tell me a little bit about that?
Shaun Mackinnon: So, as an example, the first thing everyone's taught is how to search because Talla, of course, relies on keywords, and it's one of the things we build into training. It's great to have someone who has a repository of knowledge, but that person is not always going to be there 24 seven...Talla is. So you can always go search keywords and find it.
Or that person might be in a meeting or busy, so it's always good to empower the employees. Rather than have one person who may be a bottleneck, everyone has access to Talla, everyone can search, and everyone knows how to find the troubleshooting steps.
What's the most important benefit of the Talla deployment, and how has it impacted your own role?
Rina Kremer: The most important benefit would be the agent experience. Since a lot of other functions in our company are focused on the customer experience, a large part of usually what is missed is how important the agent experience is for that. It's been great to hear since we onboarded Talla how much agents enjoy using it, how empowered they feel, and how they feel better connected to our other agent centers because they all have access to the same information, since before we had some disparate platforms and our different centers may build their own that they like using better than our old system.
Now everyone has access to Talla, and everyone is using the same information so they can all provide the customer with the same experience. So it's been really great to hear that we're improving our agent experience so they can go on and improve our customer experience.
Has Talla impacted your work personally? Has it affected team members in terms of training? Have you found it helpful in the way of training?
Rina Kremer: Yeah, absolutely, especially for my role in knowledge training and development. It's helped me to focus more on new initiatives and being more proactive in the CSM. I don't have to spend nearly as much time of my own, programming and training it and then sending it out to agents. Of course, there's the initial time investment, and you want to make sure the good foundation is there, but once it starts to really pick up on agent behavior and starts to learn and figure out all those keywords, I don't have to scale my work with how our customer base or agent base is scaling. So it's helped a lot in terms of workload for me.
How do you measure the success of Talla today? Are there particular metrics that you look at to show that it indeed has the impact you want?
Rina Kremer: We use both the internal analytical tools to the dashboard that Talla provides, and then we also always collect agent feedback at the end of every season across the board, so we're able to see how our agents are interacting with the platform or their sentiment with it, so that's how we are measuring it internally from an agent perspective.
Shaun Mackinnon: Listen to the agents; the agents will tell you if it's successful and where it needs to be improved.
What suggestions would you give to companies who might be exploring implementing something like an AI knowledge-based system or other kinds of AI to support their businesses.
Rina Kremer: I think the first really important step is to figure out your why, why are you looking for a solution, what do you want it to solve, and how will it help you. Getting those really grounding questions down before you start looking at solutions will really help since there are so many different platforms out there now, many of which don't just focus on one solution, so a lot of people are knowledge and... or CRM and.. There are so many solutions you didn't even know existed, which would be great, that's good to be open to but at the same time you want to make sure that you still accomplish what you set out to in the beginning, rather than going for maybe the shiny, fun marketing element that they have. That seems like it has a lot of potentials, but then you forget about your central agent experience or what you really need to accomplish.
So part of that is writing down all of your must-haves, your non-negotiables, or your nice to have's. If you have anything you definitely don't want to see, it's just as important as what you do want and then also separating out your how solutions from your what solutions. So say what I really want is some feedback, I really want to hear from my agents. For me, I might not really care how that's done but I just want the “what” of feedback, so that helps you not only essentially stick to what you're looking for in the beginning and making sure you get that feedback tool, but you're still open to different ways in which that can happen or ways that you can gather feedback. So just grounding yourself in your “why” and then making sure you accomplish what you accomplished while still being somewhat open to all the different solutions that are out there.
Are there things that you learned along the way that have cost you to tweak how you're using the solution or things that you might recommend that people do to make sure they are constantly improving the value they're getting?
Rina Kremer: I would say with most of my platforms now, I front-load a lot of the effort's, making sure we really take the time to build the strategic frameworks for it because ultimately if it's going to scale with you, you need to make sure your foundation is in place so it can grow, and you don't have to then either go to a different tool because it was set up poorly or because it wasn't going to scale with you, or because it wasn’t set it up correctly. You don't want to have to redo all of the structure because someone realized, oh wait, the way we set it up isn't going to support when we scale. So taking that time before you launch before you do anything to make sure that you set yourself up for whatever timeline you have for the tool, whatever that looks like, maybe a year or ten, just making sure it's tailored to your use case.
Another piece that I found really helpful, especially with AI tools, is doing a mini internal launch, as well as doing a sandbox—so inviting either potential users or other people in your organization who can get in there and start accelerating that training and the learning for AI, as well as gathering that user feedback so you can make all those little adjustments before you launch to your wider audience.
Anything else that you learned along the way, or tips you might share with people about getting users to adopt a new piece of technology, and how do you make sure things get adopted?
Rina Kremer: I would say the change management piece to that is really important. So for us, before Talla we had an add-on knowledge-based platform, so it was built into our CRM, and it was not user friendly. The information was really hard to update, it was also really hard to find even from an admin perspective, so agents didn’t trust it nor did they use it and that's what results in all those different disparate resources for each contact center. So that was some initial resistance we had to work with as well like they had knowledge before, but then they think oh that wasn't helpful, why would this do anything for me, why do I want to waste my time on this when I only have two to four months here. So you really need to prime your agents on that before they go in to sell them on why it's important, how it will help them, how it will empower them. Just to make sure that their first impression of it and their first use of it is positive, or else they may just drop it because they're not with us for the long haul, so they don't see the immediate value, and they may not use it.
Shaun Mackinnon: Of course, making sure they do have a positive experience the first time and making sure to take the time to explain it to them.
Where does the content come from, where does it live, are using an external knowledge base system? What is Talla tapping into to deliver the right information to your agents?
Rina Kremer: Yes, our information essentially lives in Talla, which is kind of its home base. When we need to create articles that come from usually different people around the organization or updates we get or what have you. We don't have it connected to another knowledge base because it is the knowledge base that we need, so it holds all that information. Our initial uploaded information came from our older knowledge base but other than that, whenever we make updates, and whenever we create knowledge we do that right in Talla, and that's where it's held.
What are some of the new ways you might use AI, and what are some AI tools in your business that you think hold promise and are excited about working with?
Rina Kremer: One direction we’re always trying to move in is pulling together our customer service support environment with our marketing environment, so making sure that whenever customers are contacting us, they don't feel like they have to go through a specific channel to do CS and then another one where they get the marketing content and figure out more about our products. So wherever they're going to get help from us, having that seamless conversation, and then getting whatever they want out of it, whether it is more product-oriented or support oriented, making sure they can do that wherever they come to us, and of course that's powered by all the data that AI can help us collect on them and the customer journey. Just bringing that whole experience together, whatever channel or whatever they’re looking for, we can service whenever they contact us.
Shaun Mackinnon: Right now, we're looking at automating reporting, more specifically to allow everyone to have the same report because right now, as an example, excel is kind of becoming online, but everyone has a different report, everyone downloads it, so you might be working off an old report, we're looking at automating and reporting to allow everyone when looking at it and then perhaps have it send every day at this certain time, which is possible right now, but we are looking at more in-depth and allowing it to actually run every report every statistic and kind of pull them all into one centralized database.
Any trends or interesting technologies you're watching in the customer service and customer success spaces overall that you're considering bringing into your organization?
Rina Kremer: I would say just the democratization of platforms and AI so that we don't have to rely so much on our Dev teams for any kind of major implementation we have. I know that's a constant struggle for us and across teams because every team seems to need some kind of touchpoint with the Dev team, and no matter how many people we hire, they're always short on time and it's no fault of their own because every team is pulling them in every direction.
So what we've started to do and even other platforms we have that we've kind of implemented that were a bit code heavy have now gone to one line of code or no code. They make updates which are just great to see because then we can continue moving forward autonomously as CS or as OPS with these new platforms and solutions, and it doesn't have to rely on someone from our Dev team coming in and taking time out of their sprint to go through all of this with us. All of our different teams can then still take on their initiatives with our own roadmap, and we don't all have to rely on going back to the dev schedule.
Shaun Mackinnon: We're keeping more towards the recruiting side of things, so we're preparing for the recruiting aspect. The thing we're looking at now is more towards scheduling and having individuals schedule their own interviews, and go through a question automatically sends to us and then, of course, the then the speed tests, because a lot of people are still working from home, so we are trying to give them the option so with all of their questions they don't have to touch base with a recruiter. With the speed tests, the typing tests, etc. it's all sent all in one nice little file, so we continue, and it is kind of touching on automation, but it saves our recruiters quite a bit of time, and we don't have to hire as many especially during the seasonal ramp-up, we don't have to hire a part-time or even three or four or seven part-time people to do the job.
Are either of you are using any automation or analytics to predict changes in your demand or consumer interests?
Rina Kremer: ROI is definitely tricky for us, it’s something we're always trying to calculate with our customer success efforts, and I feel like largely in customer success, it's harder to gauge versus marketing spend and things like that and traditionally why we get a little bit less funding then marketing and those other functions. It can also be difficult to disseminate between, okay we implemented Talla, but we also made an update to our training, and we also had a good year, we didn't have a lot of shipping delays or things like that, so it's hard to parse what exactly it was that was helping our agents so much in that year. So we do have to rely a lot more on that qualitative feedback that we get from agents where they tell us, "training was really good", and "that really helped me in this year", or "Talla was really helpful because I can't retain everything in training, so I always got what I needed, and customers are happier". Then, of course, we won't necessarily get Talla feedback from customers because they don't know we’re using it, but we can get different keywords from them, do the analytics software that we use that kind of digests our conversations and customer sentiment. We can look for things like a knowledgeable or quick response, or something like that which may indicate that it is because agents have access to this information so they can give them thorough responses that they need.
Shaun Mackinnon: So for us, it's not the actual investment as Rina said, it's very hard, especially in customer success when you have flashy departments kind of showing they were up 200%. We can't compete with the 200%, of course, but the arrow or the return on investment for us is time. For example I was able to save time, instead of working until midnight I was only working until 9 pm.
So it cut a couple of hours I've noticed kind of automating a couple of processes, especially coming in and just no reporting, no analytics but automating those processes, so they're starting to run. So time was a big savor for me.
When deploying Talla where technical resources required? How easy or hard was it to implement Talla?
Rina Kremer: For Talla we didn't use any, so Talla is the only no-code platform that we have. That was great especially given the time of it, but because nothing was required we could just push it through any season. So we didn't need anything on our end at all which is great, and it continues to be that way, so that was really helpful for us.
What's your favorite feature of Talla?
Rina Kremer: On the back end, it's really easy to build content, it's really easy to create groups, it's really easy to distinguish content between different groups, and make different levels of access and things like that. It's all very click and drag, that kind of composition. So it's really easy to do for admin, really easy to update, send out, and things like that.
Sometimes, even though I put all the content in there, even I will forget things. So I still use it to look things up once in a while, and I love the plugin feature, so wherever I am, I’m in the CRM, I'm on our Balsam web page, I just click on that, it opens a little window, I can type in my search, and it doesn't get in the way of anything else I’m doing. It really does kind of follow you wherever you want it to be but it doesn't take you out of your workflow, so that's been really helpful.