Tav Tepfer, CRO at Invent Analytics chats about the various ways through which modern retailers can benefit from AI:
Welcome to this SalesTechStar chat Tav, tell us about yourself and more about your role at Invest Analytics, how has your sales journey in the B2B tech space been thus far?
Thanks for having me! I’m Tav Tepfer, Chief Revenue Officer at Invent Analytics. We’re a retail inventory and price optimization solutions provider that helps large global retailers’ profit-optimize their supply chains with artificial intelligence (AI).
I’ve been a CRO building global sales, customer success and operations teams for the last few years and at multiple companies. I came up through product management, enterprise sales, then moving to management and becoming head of customer success then leading sales. At Invent Analytics, I lead our go-to-market strategies and am focused on adding value to our customers and accelerating company growth in North America.
I actually started as a product manager analyzing sales data. My degree is in mathematics, so I thought I wanted to be a data scientist, but I did a project for a retailer and our head of sales asked me to come with him to present the findings. On the trip home he told me I was now in sales. I never dreamed that I would end up in sales, but I love it. I worked with him for five years and he spun off to start another company and took me with him. That is how I learned that I love watching the market to see how optimization solutions can add value to customers and solve new problems. Over the years, I’ve worked for several start-up tech companies that got acquired by larger companies. I know I like the fast-paced environment where I can make a difference. I also know that your direct manager makes a significant impact on your happiness and success, so I am mindful of the culture I create when I build a team. I want my team to thrive.
As a revenue leader: what are some of the core concerns that keep you up at night? We’d love to hear about your fundamental sales and revenue processes / strategies that you have often relied on over the years to drive output as well as the revtech/salestech that you often use to power those plans?
The hardest part for me is timing. I have a plan, but customers have their own agendas and even when you can deliver significant value, they often delay for unforeseen reasons. You have to stay engaged and keep adding insights to stay top of mind.
For processes, I focus on teamwork and quantifiable activities. I align sales and marketing to the same goals. We create thoughtful messaging with multi-touch cadences and track results for our ICPs. We analyze our activities to see which ones are delivering ROI for our investment in both time and money. I’ve used HubSpot and salesforce. As long as you can track and see outcomes, both work. We always evaluate wins, losses, and delays to see what we can learn. I empower people to learn, go quickly and iterate. It’s ok to make mistakes if we all learn from them. We collaborate as a team regularly and often. Change is constant and we want to constantly stay ahead!
Tell us more about Invent Analytics’s latest AI-powered Phantom Stock app and how it’s changing the game for retailers? On the whole: how is AI revamping the core basics in inventory management and retail?
Accurate inventory data is big for retailers. It supports everything from better forecasting and planning to higher sales and happier customers. But it’s very common for retailers to have discrepancies between what their inventory system says is in stock and what’s actually in the store. When a SKU is listed as in-stock but isn’t physically on the shelf, that’s called “phantom inventory.” Of course, you can’t sell what isn’t accessible to customers. So, this leads to unnecessary stock-outs, decreased sales, and unhappy customers—which all hurt the bottom line.
The problem usually comes down to simple execution errors. Maybe an employee made a data entry mistake, or a shopper put a SKU back on the wrong shelf. Maybe an item was damaged and removed, but the system was never updated. However, spotting phantom inventory is not so simple, and store managers spend too much time and manual effort trying to tackle the problem. Some stores only do physical inventory counts a couple times a year, which means discrepancies go unnoticed and unresolved. They need a smarter way.
That’s the driving need behind our AI-powered Phantom Inventory mobile app. For years now, our team has been helping clients detect and address phantom inventory issues. Now we’ve made that service available through the stand-alone app.
Essentially, the app uses AI to predict inventory inaccuracies at individual locations, then sends weekly alerts to store managers. These alerts include a list of suspected phantom inventory, and we quantify how much sales will increase by resolving the issues. Store managers then know exactly where to direct their efforts—starting with SKUs that will make the biggest financial impact. Overall, it’s a smarter, faster, more profitable way to tackle the phantom inventory problem. In fact, our clients usually see an increase in sales of 1-2%, which is huge when you think about what that means for large retailers.
The Phantom Inventory app is just one of our AI solutions designed to help retailers make smarter inventory and pricing decisions across their stores and distribution centers. We believe the future of retail is omni-channel, and traditional rule-based inventory planning systems just aren’t enough to support inventory planners who need to make millions of decisions about thousands of SKUs, across every possible channel each day. Fortunately, AI is transforming the way retailers approach inventory planning. AI solutions eliminate guesswork and give retailers the answers they need to satisfy omni-channel customers while generating the highest possible profit.
Take us through some of the ways in which you feel retailers and merchants should be using AI powered systems to grow their bottom line as well as what precautions they should be taking if they are first time users?
AI-powered systems can profit-optimize the retail supply chain from end-to-end. When it comes to forecasting, for example, there are hundreds of variables that influence demand. It’s information overload for human planners trying to make sense of it all. Instead, AI can analyze massive amounts of data to come up with accurate and reliable forecasts—all the way down to the individual-SKU store level. Plus, AI solutions can predict how, when, and where omni-channel customers will want their orders to be fulfilled.
Of course, a better forecast alone isn’t enough to grow the bottom line. Retailers also need to apply AI and optimization for smarter decision-making. Take allocation and replenishment, for example. AI-based solutions can determine where each piece of inventory will have the highest probability of selling for the highest profit. Retailers can then optimize for profitability to get the right inventory in the right place at the right time. This AI-powered approach reduces the chance of leftover stock and painful markdowns, plus prevents early stock-outs and lost sales. AI solutions can also pinpoint the ideal time to replenish inventory and how much to send, which also reduces left-over risks at stores and early stockout risks at distribution centers.
AI systems can also optimize other types of decisions, like when inventory should be transferred from underperforming locations and which store or DC should fulfill an omnichannel customer’s order. And on the pricing side of things, AI can determine optimal promotional pricing and markdowns for each product over its lifetime to maximize sales. No matter the scenario, all these decisions are based on driving profit.
Moving on to the second part of your question, first-time AI users shouldn’t wait for perfectly clean data. All too often retailers think they have to wait for the data team to collect more data for AI to work and with optimization solutions that deliver significant value – but, since these solutions deliver significant value, waiting is costly. Instead, retailers should create a plan that can continue to layer on data to make the solution continually better over time.
Furthermore, retailers who are considering AI for the first time should think about speed to value. In other words, how long is it going to take to see any results from their investment? This is an important consideration because some AI-based solutions require complicated upgrades or replacements to existing systems, plus extensive user training. In these cases, it could take the retailer a year or more to get up—and even longer to see any real improvements. The good news is that an AI implementation doesn’t have to be long or complicated. With Invent Analytics’ solutions, for example, implementation just takes a few months. Our solutions start making inventory decisions immediately for a very quick ROI.
If there are five things that retailers and end users should keep in mind when integrating AI to enhance the overall CX, what should they be?
Inventory is everything in retail. It’s what attracts customers and keeps you in business. If you don’t have the right product in stock, you’ll lose a sale and quite possibly a customer. So, a great place to invest in AI is for inventory optimization like I discussed earlier. With an AI solution powering inventory decisions behind the scenes, omni-channel customers can get the products they want, when they want—no matter what channels they choose to shop. And it’s better to start the process sooner, rather than later because every day that passes costs money. Ultimately, retailers can drive exceptional customer experiences, with the lowest possible inventory investment.
Focus on profitability, not creating artificial rules. Most inventory systems make decisions based on gut instinct type inputs set by human planners. Even many of today’s modern systems are just today “newer and shinier” versions of the same old approach. But aiming to hit a certain service level for a category at a group of stores, for example, is likely not going to help you improve your profit margin. Instead, retailers should look to integrate an AI solution that quantifies the financial impact of inventory decisions, so they can take the most profitable path. And, don’t overcomplicate it. Yes, your business is complicated, but don’t get overly fixated on the edge cases.
Make the most of what you already have, and don’t strive for perfection when it comes to data. Adopting AI doesn’t mean you need a new data lake or to rip and replace all your existing supply chain technologies. Rather than getting into a massive, years-long infrastructure project, retailers look for a solution that easily integrates with their existing systems. The goal should be optimizing, not replacing.
Choose a partner, not just a tech vendor. A great retail planning solutions provider also serves as a long-term partner that can adjust to their needs as the system is rolled out. Retailers should choose a partner that will not only handle implementation, but also stay by their side to continuously improve system performance and uncover new opportunities for omni-channel success.
Retailers should also decide on tangible, measurable goals before integrating with AI. And, with A/B tests like those we offer at Invent Analytics, you can get started fast and start seeing that quantifiable impact right away. AI can make an impact right now. Everywhere you turn, there’s talk about AI’s potential to transform every industry. Innovative retailers around the world are using AI to transform their business and customer experience and some applications of AI have gone far beyond “potential.” I say go for it and good luck on your AI journey!
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