Starting a business is not an easy task. The time commitment and commitment is significant, and the capital outlay combined with the stress of managing multiple tasks could be overwhelming. Growing your business could be just as demanding. In addition to operational concerns, you furthermore mght need to consider managing additional labor to service the additional customers you are visiting. Every strategy session for your early-stage company needs to be thoroughly tested for scalability. Ask yourself, “Are the decisions we make today increasing or hindering our ability to scale?” Artificial intelligence can make it easier to achieve this first goal.
Let me provide you with an example: Let’s say your team has identified a problem with the way orders come into your business and also the way they are entered into your system. Sometimes orders are entered incorrectly. Some orders are entered after processing. You may have encountered cases where orders weren’t entered into your system at all.
So your team sits down to discuss how to solve the problem. One worker believes that there needs to be higher quality control when entering orders. Another wants to implement a color-coding methodology to help discover specific orders. A third wants more training for the customer support team.
While these solutions are great suggestions, they are only short-term solutions. Your job is to go searching and recognize that the real problem is growth. You have stressed the startup system to the point that future development will simply create more problems.
Many operational tasks today needs to be seen as barriers to development. When looking for solutions to handle these operational tasks, you must turn to technology. In particular, artificial intelligence and machine learning needs to be considered.
Modern technological solutions have reached a turning point and, for example, in retail, technological transformations have been progressing for years. Just think about the major point-of-sale (POS) and customer relationship management (CRM) breakthroughs that have occurred over the last decade.
When you step back and take a broad look at the retail industry, you see a heavy emphasis on data collection. The reason is easy: today’s consumers demand more personalization. Today we will predict consumer behavior and deliver automated and highly personalized messages to every potential customer. This means lower customer acquisition costs, higher customer retention, improved staff training initiatives and lower operational costs.
Below are suggestions for incorporating AI and machine learning into your retail operations to scale:
Understanding pain points
Before you dive deeper into AI and machine learning, you would like to understand the business’s weak points. This doesn’t necessarily mean only your own problems. It also addresses problems and issues that affect your industry.
As the founder and CEO of a dog grooming salon, let me provide you with a relevant industry example: Treatment planning is one of the most significant barriers to scaling up effectively and profitably. Different breeds have different needs and due to this fact require several types of treatment. Not all of them arrive in the showroom in the best condition. It might take one person an hour, one other three. This could cause delays in your schedule and leave you scrambling for the remainder of the day. This could result in the lack of clients if you are unable to keep appointments.
Build your solutions
Once you have a higher understanding of your key issues, you may start building models that may make it easier to scale your business efficiently and profitably. As artificial intelligence and machine learning have change into more available, it has change into much easier to create useful models to help overcome retail challenges. Plus, with machine learning, these models will proceed to evolve as more data is consumed and latest challenges come your way.
Here are two AI solutions that entrepreneurs should consider:
- For talent recruitment: PARADOX — Automate candidate screening to make sure you’re not wasting time on candidates who don’t meet your organizational or cultural goals. PARADOX can quickly screen candidates and select the top five based on your requirements.
- For sales automation: : CROSS – The problem with many leads is often that the leads are not buyers. You could also be spending as much time chasing unqualified leads as you are pursuing real customers. This is where EXCEED might help. Each potential client goes 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 artificial intelligence and machine learning include:
- Customer service chatbots
- Face recognition
- Dynamic pricing truly based on supply/demand
- Replenishment and inventory management
Using artificial intelligence and machine learning beyond sales
As many entrepreneurs know, the customer journey does not end when they leave the store. To scale profitably, it’s essential to invest in building relationships with your customers so that they proceed to come back and use your products or services.
Artificial intelligence and machine learning might help in this area of your business. Marketing automation is just one example and could be implemented through electronic mail, personalized web messaging, social media posts, or good old-fashioned SMS.
Providing personalized service is the way to retain customers. However, this requires a lot of practical effort and without the use of technology. Artificial intelligence and machine learning can automate your campaigns and take control of repetitive tasks without damaging customer relationships. If used accurately and provided enough data, it will possibly make it easier to scale your retail business to latest heights in an efficient and profitable way.
Key takeaways on using artificial intelligence and machine learning to scale your business
Remember that engaging potential customers is not unique to your company. Every competitor tries to acquire latest customers. In some cases, these latest customers could also be your existing customers.
Better customer data is only a part of the development solution. You need to find automated solutions that may quickly synthesize data and then deliver personalized shopping experiences that drive engagement. Artificial intelligence offers promising solutions for the inspired business owner.