The price of light is less than the cost of darkness.
Arthur C. Nielsen
Without data analytics, a business on the web can be likened to a deer in headlights. The cost of darkness is indeed very high, versus the cost of investing in a solid data analytics solution.
When looking at your budget, setting up data analytics provisions can be one of the best investments you choose for your company. Data analytics will drive informed decisions, which can help just about every aspect of your business. Let’s look at some of the areas where data analytics shows proven return on investment.
Data Analytics Improves Products
Data analytics can improve products in all stages of a product lifecycle. Product conceptualization using data analytics directly addresses customer needs. Initial ideas can be floated for audience response, and new data integrated to improve concepts. Predictive analytics can take current sales statistics, combined with market research, and predict how a new product will perform, taking the guess work out of new product selections. In book marketing, knowing complex statistics on which types of books are selling well and which of those sub-genres have gaps in the supply can help publishers position new books with more chance of success.
Product design using data analytics means better materials, better quality suppliers, and lower costs. Design analytics can improve features based on comparative research, and analysis of early test data can help solve faults before release.
Launch and post market analysis can help provide product improvements or spawn complimentary products from customer feedback, return statistics, social media, insights into which products are selling better in what markets, which features work well, and which are problematic.
Analyzing current sales versus costs can determine which products don’t work and why. Lower performing lines can be discontinued to allow room to grow better performing ones.
Data Analytics Improves Customer Service
Reviewing customer feedback, call center interactions, consumer surveys, social media, and buying trends with analytics can help improve a companies customer service significantly.
Knowing what your customers’ needs and behaviors are can help you target your products and services to match them. Tracking frequent customers, high spending customers, or new customers can provide opportunities to send them welcome packages or loyalty specials.
Knowing what your customer’s chief problems are, logging interaction, and correlating this with demographics, geographic, and spending data can help you tailor services directly to their needs.
Data Analytics Improves Productivity
Data analytics can help improve productivity by analysis of various processes surrounding a companies product. This could include:
- Analyzing material waste in product creation to identify possible improvements to processes;
- Analyzing time spent on various parts of the production to determine if there are bottlenecks;
- Comparison of employees productivity to identify training needs and improve the capabilities of human resources;
With data analytics, any number of measurable parts of production and business processes can be analyzed for improved productivity.
Data Analytics Helps Refine Marketing
The retail and hospitality industries have developed ways to use data analytics in their marketing and pricing to a fine art, for example, Target’s data analytics helped them predict pregnancy terms to time sending out coupons to suit new arrivals. Analytics were so accurate, in one case Target had rather embarrassingly found out about an impending arrival before the girl’s parents.
Airlines and hotels use data analytics to improve pricing and maximize bookings. If analytics show increase in demand for sectors or dates, pricing can be increased, likewise empty slots prompt specials and discounts in a time matched manner, as the dates get closer increases or decreases in pricing become more significant.
A more diverse application of data analytics in marketing is provided by a clothing company, Bravissimo, in the UK. The company tied weather forecasting data into it’s PPC (pay-per-click) campaign to know when to say target swimsuits effectively, and when people were more likely to be indoors. The innovation reportedly gave them a staggering 600% increase in sales in the three summer months compared to the previous year.
These are a few of the many examples of how knowledge through data can significantly improve marketing.
Data Analytics Drives Predictions
Analytics can help create predictions on consumer demand for products, emerging markets, resource needs, and many other items important for business operations, with far more accuracy.
Investing in a new direction for business can be extremely costly, and if it’s not done with analytics, there’s a hit and miss chance of failure.
Customer surveying is not enough to gain predictive insights, one has to compare multiple information sources, which is what data analytics can do. Data analytics, for example, has allowed us to see that there is, not surprisingly, a notable gap between what customers say they want, and what they actually do. This could be from a false image, impulse buying, or a mismatch in desire versus capability. If relying on survey data alone, a false premise can easily be created. It is certain that proper data analytics using multi-channel resources can bridge the gap and dictate customer’s behavior with surprising accuracy.
Predictive insights can also be used for improving productivity in areas such as stock ordering, scheduling maintenance, planning transient staffing, working out shifts or downtime.
Data Analytics Solves Problems
Data analytics provides insights which can be used to solve problems. One budgeting app totally turned it’s sales trend around by analyzing usage and drop-off data. Analytics determined the problem area was getting customers to link bank accounts. If they didn’t drop off rates were huge. Obtaining this data allowed the developers to focusing on making it easier for customers to link accounts, providing prompts for this action in early interaction. The new measures increased bank account linking, and as predicted drop off rates reduced, solving the problem.
A chain of fast food restaurants in the US uses complex data to solve problems quickly, for example oversupply of a short shelf life item triggered marketing specials in the affected area, under performance of revenue in any branch could trigger automatic requests for operations or training specialists to address deficiencies.
The more we know, that is the more properly analyzed data we have, the more problems we can solve for our business.
Data Analytics Helps in Risk Analysis and Fault Prevention
Data analytics can help in risk analysis to improve quality control, reduce workplace accidents, and combat fraud.
Identifying patterns can help to identify the hazard behind certain safety events. For example, the number of accidents that occur in the midnight to dawn shifts can be correlated with the amount of driving, traffic, and work shifts, to determine if fatigue is a contributing factor. Occurrence numbers will help set target and alert levels to determine if safety is effective. Production quality issues can be resolved in a similar way, for example, do the majority of manufacturing faults really occur on Monday mornings or Friday afternoons?
Identifying common areas for faults through analytics means they can be fixed at their root cause and improve overall levels of quality and safety.
Data Analytics Helps Keep Track of Competition
If your business is to be successful, there’s no doubt that you need to know how your product compares to your competitors. Competition analysis drives product development, pricing, and marketing. Tracking competitors across multiple platforms such as social media trends, product popularity, revenue trends in product lines, can help businesses gain a competitive edge.
A survey by Mckinsey and Company in 2016 showed that the majority of companies who are ahead of their competition in a market sector make extensive use of data analytics, almost double the amount who didn’t. Deloitte found that 90% of companies felt analytics improved competitive positioning, with 25% saying it provided significant improvement.
Data Analytics Drives Growth
When business managers have proper access to good data analytics, they can make decisions that promote growth.
Data analytics can tell us whether the new capital investment will pay back its purchase price and in what time frame. It can help us determine if adding a new location will help sales, and provide facts behind which location will be best to use. Data analytics can project market growth, and our likely share in that based on multiple variables such as investment in marketing, new technology that will expand the market, and our trending market position, to drive investing decisions. Analytics streamline businesses profits, freeing up expenditure, and provide ideas for new products, driving growth.
Data analytics helps a company see behind the figures to the deep insights they contain. It helps improve your company’s performance and helps improve your customers’ experience. Investing in data analytics is not only the best choice, it’s imperative if you want to grow in today’s economy. The question you need to be asking next is which parts of data analysis best suit your business and how to implement them.