For any organization to understand the target audience has become convenient, thanks to the exciting feature of predictive analytics. But, the tool of predictive analytics isn’t enough as it lacks the insight of behavior of the customers. Especially when one doesn’t know whether the product would be successful or not and plan strategies accordingly for communicating to the customers.
Data Analytics is crucial in terms of understanding the customer behavior and to pick the correct data from the heavy influx is itself a strenuous work. The reason why it is important to know the pattern of the analytics, there are many ways in which you can make the predictive analytics. Here’s a rundown:
1] Driving more traffic and receiving incentives:
It takes a lot of hard work to bring loyal customers back to your website, since there are always a lot of temptation that can distract them. With the help of a predictive model, one can easily interpret which customers are returning and has the potential to be a long-term user.
2] Resonating with your Customers:
Harnessing the insights of predictive analytics to make your customers use your products and services. For example: In Fashion industry, there are several fashion shows that showcase new designs and dresses and capture attention and it requires to go that extra mile to establish new connections. WIth the help of predictive and analytic solutions, fashion retailers easily understand where the consumers’ interests and tastes lies.
3] By Executing Big Data:
Big Data can go a long way in transforming all the major key aspects. Sometimes, even though we have all the data we can’t bring about any major changes as it is the only way to make all the data coherent. Many retailers can gain insights from learning what exactly their customers need, according to their shopping practices and thus assuring more conversions.
4] Enhanced Customer Service:
With the predictive analysis, you can make the correct marketing strategies for your business. Once you know the exact needs, interests, likes, dislikes of your customers you can take decisions that could yield more results on social media marketing and answer on-site queries.
5] Set the Correct Price:
Since the data collected is accurate, it would help you know the correct price for your products. In this way, not only your customers would know what exactly to pay for your products, but also optimizing the same by studying your competitors. The competitors can check the inventory levels, study the product pricing as well as collating demand. Even if there are changes in the market, you can still keep your customers intact for real time.
6] The Right Shop Location:
For opening up of a branch retail store, it is crucial to select the place wisely. Any random place won’t get you customers at any particular location. Predictive analytics would tell you where the customers hangout mostly and with the analytics based on demographics, market conditions and customer’s purchasing power. As you follow the trends in the predictive analytics, you know exactly which city would be best-suited for you.
7] Promotional Offers:
Though it is easy to learn about the lifestyle and habits of the customers by analyzing their behaviours, it generally leaves a trail when they make several online and offline purchases. Collecting this data from the predictive analytics to gain insights on their behaviour, it is needed to anticipate the following needs. It is important to know the kind of promotions and would be suitable to introduce as one type of promotion is good for seasoned customers, while something else is good for new customers. Integrating attitudinal and behavioural information using predictive analytics would help draw answers on what and why of consumer choices and how you can focus on personalized promotions.
Promotional Offers can get you a higher engagement rate and is relevant to the customers, through predictive analytics. Drawing insights on “what” and “why”, predictive analytics is a huge help for the retail industry as it can help you relate to customers’ requirements.