Sales trend analysis

Timely identification of newly emerging trends is very important to businesses. Sales patterns of customer segments indicate market trends. Upward and downward trends in sales signify new market trends. Time-series predictive modeling can be used to identify market trends embedded in changes of sales revenues. Understanding of sales trends is important for marketing as well as for customer retention. Typical sales trend analysis includes;

• Which customer segments are having highest growth in dollar terms?
• which customer segments are having highest revenue decline in dollar terms?
• Which customer segments are having highest growth rates in percentage terms?
• Which customer segments are having highest revenue decline rates in percentage terms?
• How solid the growth (or decline) trend is?
• Which customer segments are showing exponential growth (or decline)?
• and so on.

Trends may be categorized as;

• Short term trends capture rapidly emerging trends.
• Mid term trends capture trends developing in between.
• Long term trends capture trends developing over long periods.

Sales forecasting

Regression is a data analysis technique used in developing predictive models for numerical data. It automatically derives mathematical functions that summarize trends embedded in past historical data, in such a way that minimizes the errors between actual input data and predicted values by the models. Regression can be applied to time-series data. A time-series consists of a set of observations which are measured at specific time intervals, say, monthly, quarterly, yearly, etc. Observations we are interested are sales revenues.

Customer (or market) segments have different sales trends. Some segments may be growing, while others are declining. Segment-by-segment sales forecasting can produce very useful information. Forecasting can be short term, mid term and long term. Long term forecasting may not produce accurate predictions. However it is very useful in understanding market trends. StarProbe develop best sales forecast models for each customer segment. It automatically select a best model out of linear, exponential, square-root, and various polynomial functions.

Segmentation for trend analysis

Market segmentation is a process that divides a market into smaller sub-markets called segments. Normally, market is segmented in such as way that customers of a segment have the same attributes. Commonly used attributes in segmentation include the followings;

• Products.
• Product and service types (or product categories).
• Geographical regions: regions, countries, states, zip-codes, counties, etc.
• Demographics: gender, age, income, education, etc.
• Psychographics: life style classification.
• Sales channels, branches, and departments.
• Sales representatives.
• and so on.

The following figure shows sales trends by segment. The sky-blue bars represent recent sales figures. The red bars indicate next three term forecast. "Trend(3)" uses three recent figures for modeling. So it indicates short-term trends. "Trend(6)" uses six recent figures to show mid-term trends;

Trend Analysis and Forecasting Software

StarProbe Data Miner Web Service Kit provides a platform for building trend analysis data warehouses, containing sector-by-sector trend histories. Trend analysis data warehouse can be analyzed with easy-to-use browse tools which can provide various trend analysis and forecasting information. For example, (short-term) sales forecasting, growth rates, growth percentages, trend significance, trending types, and so on. Use of trend analysis includes;

• Sales trend analysis - revenue and volume analysis.
• Product sales trend analysis.
• Market trend analysis.
• Equity (share) price trend analysis.
• Accounting trend analysis.
• Work force recruit forecasting.
• Healthcare fraud detection.
• and so on.

If you are interested in trying with your sales sales trend analysis, please write to us.