How data from Online Reviews and Macroeconomic indicators used to predict product sales forecast

Research paper

How data from Online Reviews and Macroeconomic indicators can be used to predict product sales forecast TAGSData analysis, Logistics, Supply chain management, Research methodology, Macroeconomic indicators, Data collection, Statistical analysis, Research methodology SERVICESResearch Planning | Data Collection | Semantic Annotation | Business Analytics | Bio Statistics | Econometrics

IN BRIEF

Online Reviews and Macroeconomic indicators.

A unique technique for product sales, predicting macroeconomic indicators and online reviews.

INTRODUCTION No matter what supply chain management, ordering, manufacturing, or logistics, the summons facing industries is random on demand. Enterprises create inappropriate production choices that supported the chance in the distribution of the request causing huge losses and cut back the company’s proﬁts. As a result, the demand is plagued by several factors and is commonly not accomplished in theory. Sales prediction is a crucial part of trendy business operations which will increase the economic welfare of endeavours by visual impairment within the production set up.

Online Reviews With the advancement of Web2.0, folks can suitably post their point of view of products on social media and commercial internet sites. This user-generated specifies the actual voices of consumers who use the product in varied situations, and these reviews are user familiarized. It's a research-based methodology and sensible selection for dealers to predict product sales via reviews in online platforms. The comprehensive studies have specified that online reviews have a significant influence on product sales.

Contd.

Researchers invented a synchronous equation system to find out the link between online reviews and the revenues of films. Hence, degree of online posting includes a significant influence on box office sales. Online user reviews are potential indicators of viva-voice power and play an essential role in box office sales. Online reviews have a significant influence on hotel bookings. Excellent online reviews will considerably enlarge the number of hotel orders, whereas bad online reviews can lessen the number of hotel reservations.

The interactivity effects of online surveys, promotional ways, and online sentimentality have a major role in sales. Briefly, online reviews have a decent hold up for sales forecasts.

Older Adults

150

40 0.8

30 0.6

20 0.4

10 0.2

00

-29.3

-0.5

+0.5

+29.3

Product Quality

Prop. of Part. choosing the higher rated product

Younger Adults 40 0.8

30 0.6

20 0.4

10 0.2

00

-29.3

-0.5

+0.5

+29.3

Product Quality No single review Single postive review Single negativereview

No single review Single postive review Single negativereview

Fig 1:Proportion of participants choosing the higher rated option by review condition and product quality for young adults (left panel) and older adults (right panel). The product quality index indicates the quality of the higher rated option

Macroeconomic indicators Macroeconomic indicators are often published at a shallow frequency. The sales prediction strategies whether or not the standard measure strategies forecast methodology supporting online reviews, principally use previous sales data collection to predict the sales in the future. However, there's a precise physical phenomenon quality. The macroeconomics situations, like CPI, not only would affect customerâ&#x20AC;&#x2122;s temperament of shopping additionally contain progressive environmental data.

Contd...

Once firms build production plans, they ought to observe the condition of the market and enquire the development or future assumption of economic indicators. Macroeconomic indicators are issued at a minimum frequency that makes them too slow to predict, and they can enhance prediction results and the drive for sales within the medium to future.

Select proper macroeconomic indicators

Calculate sentiment indices based on online review

Construct the forecasting model

Estimate the parameters of the models and measure the performance of the models

Experimental analysis

Fig 2: Research Framework

Predicting product sales forecast using Online Reviews

E-commerce companies recognize the significance of analyzing the online reviews of their products. Studies demonstrated that for piloting analyses for online reviews, Polymerization Topic Sentiment Model (PTSM) can be applied to extract and filter the data from online reviews. Through integrating this model with machine learning methods, results in showing that the forecasting accuracy had been upgraded. The experimental results shows filtering topics hidden in the reviews are more significant in influencing sales prediction, and the PTSM is more exact than other ways. The findings contribute to the knowledge that filtering the topics of online reviews could improve prediction accuracy.

Conclusion Big Data sets provide new and useful sources of information for economic analysis, but also warrant further refinement, development and monitoring in parallel with other macroeconomic indicators and forecasting techniques. Concerning online reviews, we tend to not only contemplate numerous indicators of online surveys, however additionally think about considering taking into account the user’s negativity bias about online reports, which indicates that buyers additional sensitive to negative reviews than positive reviews. Prediction exactness of this technique is beyond that of the comprehensive strategies, and it's confirmed by removing every a part of the model singly that the factors thought of having a significant impact on the model’s performance. Sensitivity analysis and detection additionally specify the prevalence and hardiness of the strategy. The suggested methodology is vital for developing strategies of product sales prediction on macroeconomic indicators and online reviews.

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