In a recent interview with Karen Webster of PYMNTS, Osama Bedier, the ex-Google Wallet exec who founded Poynt smart terminal, made a profound announcement:
You have to be a technology company to be in retailing in the future
What does this mean?
Retail margins are not getting higher. There’s more competition from online sources, there’s more price transparency with global economies, and to underscore that the US restaurant market has not even kept growth with inflation.
In a nut shell, retail has less room for error than ever before.
To succeed, retailers (all brick and mortar operators) will need to use technology. This is especially true as data-savvy retailers like Amazon enter the physical world. According to soothsayer and NYU professor Scott Galloway, the future of retail lies in a combination of physical and digital presences. Scott rationalizes this on logistics alone: Amazon spent $6.6 B on shipping and received only $3.1B in shipping fees.
As a service to merchants everywhere, we’re creating a checklist of technologies that they should be thinking about as the industry moves forward. The internet has democratized solutions, meaning availability is higher than ever while prices continue to drop. If you don’t put the time in now, you won’t have the time to reconsider later.
Marketing Solutions
- Price elasticity: what are the pricing relationships between items and how should prices be changed to maximize revenue? Purchase volume data can be mapped to loyalty information or credit card/mobile purchase data to determine what offerings are repeat winners while which should be axed immediately… if you have the right POS, of course. Example: because socks and underwear sell well together, increasing the price of underwear by 10% while decreasing the price of socks by 5% will drive 5% increase in revenues.
- Promotion measurement: if you ran a promotion, did it work? Uncovering relationships and ROI will help determine when and what type of promotions to run in the future. Ensure that these solutions are using machine learning to optimize their efficacy. You can only get this to work if you choose a POS that shares such data. Example: is your happy hour actually worth it? If not, when should you run it, or how much should you discount bar orders to be economical?
- Mobile applications: we see zero evidence to put any money here. You need to have a very good reason to build and app because they are very expensive and time-consuming to manage. If you have a huge brand (like Starbucks) then an app might make sense. But remember – Starbucks uses its app to collect customer data and allow customers to order ahead. Why are you building an app? You need a legitimate business reason.
- Loyalty: wisely used, this can be a boon; ignored and it will be a total waste of money. Make sure the loyalty program is integrated to your POS (a very expensive task if you own a legacy system), otherwise you will be doing much manual work to calculate the ROI of your efforts. Example: did my loyalty members increase my revenues to drive positive ROI for my program?
- Online ordering: as the economy demands more convenience, ensure that potential customers are finding you where they look to spend money: Yelp, Google, Amazon, and others. At a minimum you need your own online ordering presence, even if it’s only hosted on your own website. Make sure you do the math for third party services that charge large percentages of each transaction and refuse to share customer data – these are warning signs for a new-age Groupon. If your POS cannot connect to ordering providers, don’t bother: you’re only making more work for yourself and introducing more opportunity for error. Example: if a customer is looking to buy a red sweater on Google Shopping, are your red sweaters listed as a local option?
- Delivery: the jury is still out on the economics here. Don’t swallow the entire cost of delivery thinking the market is forcing you to – that’s just silicon valley hype. One thing is clear, however: [bctt tweet=”merchants cannot execute delivery as well or as cheaply as data scientists who only do delivery” username=””]. By using third parties you’re “renting” delivery capabilities which are on-demand, more reliable and cheaper. These will be the first services to drive down costs with automation and most come with cool tracking features for customers. Like online ordering, delivery should connect to your POS orders seamlessly. Example: if customers want the items delivered, how does that happen?
- Busy-ness: per the above, consumers are thinking critically about their time. Order-ahead technology is growing at 57% CAGR, expected to reach nearly $40B by 2020. This has given rise to online ordering and delivery services at billion-dollar scale. All of this commercial activity, however, starts with the transparency of when you’re busy. Whether you want it to happen, Google (and soon Apple) are showing consumers when you’re crowded. Example: how busy will this place be in an hour; if it’s too busy let’s just go somewhere else. Accurate information starting with your POS data gets the wheels rolling for commercial activity like:
- Reservations and wait lists: don’t spend thousands of dollars on wait list management software when there are acceptable solutions that are nearly free. Ensure that any customer data being generated by the third party provider is owned and available to you.
- Yield management: hotels and airlines have nailed the marriage of price and scarcity. As your peak times become transparent, there will be ways to tie instantaneous pricing and promotions to make the best use of your assets. Several startups are on this path already. Example: if I lower prices when I’m slow, is it a good move?
Operational Solutions
- Labor management
- Labor forecasting: using data science to predict customer demand and staff accordingly. Overstaffing is a hit to profits while understaffing injures revenues through poor customer service. Forecasting solutions should be hands-off: managers and owners cannot understand wind speed correlations to revenue as well as machines. Only use solutions that employ real data science and make sure your POS system can communicate the requisite data with any provider. Example: how should I staff next Thursday at 10:00?
- Employee scheduling: employees have unique abilities; some are great for high demand hours while others thrive in slow environments. Find solutions that recognize personal patterns in POS data and can recommend the right employees for the right shifts to maximize your revenues. Example: when should I work Jane Doe to maximize her potential and what will that mean to my bottom line?
- Employee-customer relationships: some employees are so good they can create repeat customers… give customers a reason to shop instead of choosing Amazon! Using payment and POS data, you can find such trends. Example: which employee is responsible for driving repeat sales, or, when what employees work together do we get the most out of our business?
- Inventory management
- Inventory forecasting: like labor forecasting, inventory forecasting requires real data science to be useful. Obviously you need a system (ie POS) that collects inventory data and makes it available. Once you’re there, find a solution that accurately produces just-in-time inventory. Example: how much sauerkraut should I order for next week?
- Leveraging suppliers: suppliers have helped retailers for decades. Unfortunately, many retailers simply don’t give suppliers the data they need to help them be more successful. With better information, suppliers can apply big data techniques to give you insights into item trends, average pricing, promotional efficacy, etc. You should have a POS system that captures relevant information and allows easy sharing with your partners. Example: should I add paleo tacos to my menu?
- Business loans: loans are a function of risk. If you can prove you’re using better technologies, you will earn more money and drive down your cost of borrowing. Further, by pooling data with other merchants through the right partners, you can avoid expensive cash advance instruments and get securitized loans from underwriting banks. That’s the difference between 20% APR and 5% APR. You must choose the right POS systems to help you share data and make this possible.
- Payments: there’s a lot of marketing hype around mobile payments. Through our studies it seems that mobile payments do not yet solve a real business problem. They do help you collect more customer data, and if you’re looking for a convenient way for customers to enroll in promotions, loyalty or order ahead, mobile payments can be a component. But really, there’s nothing here yet. Ensure that your POS can accept mobile payments when the market is ready. Unlike some other operational tools, there’s only a nebulous ROI today.
- Data correction: it’s not a secret that 85% of customers are looking for businesses online. Much business listing data is incorrect – about half of it. Inaccuracies cost merchants over $10B in sales opportunities. Fix this data now. Your POS company has access to your information and can update it on your behalf – this assumes you’re using a POS from the right provider. Example: is my phone number right on Google? What about my hours of operation and specials?
You should have noticed a trend in these solutions: they require quality data coming from your POS. Many POS companies will not share any data, particularly legacy providers, starving the business of the necessary tools to stay relevant in a hyper-competitive market.
Buying a POS is the most important business decision you can make. Don’t let anyone tell you otherwise.
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