Customers have a lot of expectations, one of which is hyper-personalization. They expect both the convenience and flexibility in where they can place orders from and how fast they receive them. They would also like to see offers that cater to their needs.
As a result, today’s recurring trends include big data, visual analytics, and hyper-personalization as an attempt to cater to the needs of buyers.
Retail Analytics and the Basics of Big Data
The most prosperous retailers use up-to-date and large volumes of data, also known as big data, to base their pricing and marketing efforts. Big data is a lot of data that’s high in velocity as the majority of it is produced in real time. Data-driven pricing and promotions have proven to be much more precise versus expert-based decision-making. Retail data analytics provides some opportunities surrounding strategic planning, routine operations, and interactions with customers. Manual data collection and processing isn’t sustainable anymore which is why retailers need to start making changes.
1. Going Visual
The visualization shows where there are room and potential for growth. Companies can identify opportunities right away and examine performance in only 10 minutes through visualization. Sharing that information in the traditional form isn’t very useful, especially when market studies contain many complicated indicators.
Visualization makes data more meaningful as well as illustrative, so you can better gain the attention of the audience and create more dependable partnerships as it’s much simpler to understand the main problem.
The Japanese company, GooDay, has put forth this method on a grander scale which, in return, has made their sales increase and their inventory levels to decrease.
2. Altering Settings with AR
Augmented Reality, or AR, is another example of visualization. According to the Accenture Augmented Reality Survey (2014), less than a quarter of buyers didn’t see how AR would benefit them. However, today, the 2018 Accenture Digital Consumer Survey of 21,000 online consumers in 19 countries states that buyers want more digital experiences blended into everyday life. According to the same report, 61% of respondents indicated that they want to visualize how clothes might look on them via VR/AR. All industry leaders are using some form of AR. For example, the app, IKEA Place, takes advantage of AR to allow users to see how various products will go with their spaces. The best part is that the visuals are now dynamic thanks to character rendering, videos, as well as 3D modeling which, in turn, enhances buyers experiences. Another example includes an app based on the series “The Walking Dead” from the combined efforts of AMC and Mountain Dew. Together, they engage customers as they have to chase after new “walkers” which can be unlocked once a packaging of Mountain Dew is scanned.
3. Taking Advantage of Machine Learning
Both artificial intelligence and machine learning are the two trends that let us gather a whole bunch of information. AI assistants adjust to shoppers and train themselves for specific ones as customers now yearn for personalization. AI and neural networks are also useful in regards to both dynamic pricing and precise demand prediction. In other words, industry leaders utilize smart algorithms to examine market events and predict potential changes and customer behavior.
One such example is Sony Pictures Home Entertainment. They’ve integrated it into their general strategy which has helped them to boost their sales and at the same time mitigate risks.
Machine learning doesn’t merely revolve around analytics, though. It also, for instance, can change the way we shop; take a look at Amazon. With their Amazon Go stores, you no longer need to check out. Also, Amazon’s Recommendations Engine accounts for as much as 35% of the giant’s revenue as it crafts the optimal prices for individual consumers based on their purchasing history.
4. Depending on Robots
To automate as much as possible, Amazon has also been putting money into robots that do physical work. This versatile AI software can recognize objects and interact with them. By 2017, one-fifth of their fulfillment centers were utilizing them. Nike has also begun innovating by funding Grabit, a robot developing startup which, with time, was able to assemble the top part of shoes in under a minute. Manually, that typically takes 20 minutes.
However, not all robots are visible; take for instance chatbots. However, they are something consumers would like to see more.
5. Getting Rid of Boundaries
To see the best results, combine what you’ve learned earlier. This lets retailers seamlessly manage all of their processes as they don’t have to go from one application to the next. With the help of a phone, retailers can use apps that gather data analytics, manage workflow, visualize statistics, and plan the following steps. Also, they are only becoming more straightforward to use.