Starting a business is no easy task. The commitment and time sacrifice are significant, and the expenditure of capital combined with the stress of managing numerous tasks can be overwhelming. Growing your business can be equally as challenging. In addition to facing operational issues, you also need to take into consideration the management of additional labor to cater to the extra customers you’re seeing. Every strategy session surrounding your early-stage business should be squarely tested against the backdrop of scalability. Ask yourself, “Are the decisions we make today increasing our ability to scale or hindering our ability to scale?” AI can help you achieve the former.
Let me give you an example: Let’s say your team has identified a problem with the way orders come into your business as well as the way they are entered into your system. Sometimes, the orders are entered incorrectly. Some orders get entered in after they are processed. Maybe you have experienced cases in which orders were never even entered into your system at all.
So, your team sits down to discuss how to fix the problem. One employee thinks there needs to be better quality control around order entry. Another wants to deploy a color-coding methodology to help identify certain orders. A third wants more training for your customer service team.
While these solutions are great suggestions, they are merely short-term solutions. Your job is to look around and recognize that the real problem is growth. You have stressed the startup system to a point that future growth will simply create more issues.
Today, many operational tasks should be viewed as growth barriers. As you seek solutions to handle these operational tasks, you should turn to technology. Specifically, consider artificial intelligence and machine learning.
Modern technology solutions have reached inflection points, and in retail, for example, technology transformations have been in progress for years. Just think about the major leaps point of sale (POS) and customer relationship management (CRM) solutions have made in the past decade.
When you step back and take a broad view of the retail industry, what you see is a great focus on data capture. The reason is simple: Today’s consumers demand greater personalization. And today, we can predict consumer behavior and deliver automated and highly customized messages to each individual prospective client. This means lower customer acquisition costs, higher client retention, improved staff training initiatives and lower operating costs.
Below are tips for incorporating AI and machine learning into your retail operations to scale:
Understand the pain points
Before you start looking further into AI and machine learning, you need to understand the business’ pain points. This doesn’t necessarily mean your own issues exclusively. It also refers to problems and matters that relate to your industry.
As the founder and CEO of a dog grooming salon, I’ll provide a relevant industry example: Treatment scheduling is one of the most significant barriers to scaling up both efficiently and profitably. Different breeds have different needs and, therefore, require different types of treatment. Not all of them come into the salon in the best condition, either. One may take an hour, while another might need three. It can put you behind schedule and leave you chasing your tail for the rest of the day. The impact of this is you may end up losing customers if you can’t keep your appointments on time.
Build your solutions
Once you’ve got a better understanding of pain points, you can begin building models to help your business scale efficiently and profitably. As AI and machine learning has become more accessible, it’s made it much easier to build useful models to help overcome retail pain points. Plus, with machine learning, these models will continue to evolve as they consume more data and new challenges emerge on your business’ journey.
Here are two AI solutions that entrepreneurs should consider:
- For recruiting talent: PARADOX — Automate the screening of candidates to ensure you are not wasting time with applicants who don’t meet your organizational or culture goals. PARADOX can quickly scour applicants and select the best five based on your requirements.
- For sales automation: EXCEED — The problem with many sales leads is often that prospects are not buyers. You may be spending just as much time chasing non-qualified leads as you are chasing real customers. That is where EXCEED can help. Every lead gets funneled through a qualification process that is personal, conversational, friendly and completely automated. Real leads are immediately connected to you or your sales teams for closing.
Other clever uses of AI and machine learning include:
- Customer service chatbots
- Facial recognition
- Dynamic pricing that is truly supply/demand-based
- Restocking and inventory management
Using AI and machine learning beyond the sale
As many entrepreneurs know, the customer journey doesn’t end once a customer leaves the store. To scale profitably, you need to invest in building relationships with your clients so they continue to return and use your products or services.
AI and machine learning can assist in this area of your business. Marketing automation is just one example and can be implemented through email correspondence, personalized web messaging, social media posts or a good old-fashioned text message.
Providing a personalized service is how you will retain customers. However, this requires a lot of hands-on effort without the use of technology. AI and machine learning can automate your campaigns and take control of repetitive tasks without compromising the relationship with your clients. If used correctly and provided enough data, it can help scale your retail business to new heights in an efficient and profitable way.
Key takeaways on using AI and machine learning to scale your business
Remember, engagement of prospective clients isn’t unique to your business. Every competitor is out there trying to win new customers. In some cases, those new customers might be your existing customers.
Better customer data is only part of the growth solution. You need to find automated solutions that can synthesize the data quickly and then deliver personalized shopping experiences that drive engagement. Artificial intelligence offers promising solutions for the inspired business owner.
Originally published Aug. 9, 2021.