However, shopping malls have been monitoring consumer foot traffic and behavior for many years using people counters, security cameras, heat maps, and undercover researchers. Retailers not only use this data to strategically place items in their retail storefronts (i.e. placing chocolate bars and other small goodies by the cash register) but also to determine their best sellers and prices. These forms of tracking consumer behavior can ultimately impact a retailer’s success in reaching their target market.

Many eCommerce websites also track customer traffic on the web, collecting shoppers’ names, purchases, and recent items they’ve viewed. Some even target consumers with ads after they leave a website. By combining the data with their own sales, stores in these malls can gain better intelligence on how to improve a consumer’s shopping experience, especially during the holidays. With more and more people using smart phones, it is inevitable how mobile data will influence tracking consumer behavior in the future

One perk for shoppers is that they no longer have to save and print out coupons from emails!

Through their mobile phones, shoppers can receive texts about sales and coupons as they enter stores. They can keep track of their favorite stores and make a purchase anywhere/anytime. One perk for shoppers is that they no longer have to save and print out coupons from emails! All they have to do is show the coupon on their phone at the point of purchase to redeem their coupon.

With “QR” bar codes or quick response codes directly on coupons on your phone, savings can be redeemed on the spot. While many people don’t know yet that they can use QR codes on a mobile device, retailers have only begun to take advantage of this technology and more customers are now able to scan items in a store and pay for it using their mobile phones.

While it’s just the beginning of a new era, mobile marketing is taking us by storm and now is the perfect time to put this trend into effect.

• Who is responsible for all of the data?
• What problems exist with the data?
• What requirements need to be in place for quality to be at its best?
• Can a return on investment be quantified in such a case?

This is where Data Quality Management (DQM) comes into play. The goal of DQM is to establish roles, responsibilities, policies and processes to attack data quality issues. Cooperation and discipline is essential. It is important that everyone recognizes problems with the data and participates in determining a solution. Specifically, the IT department plays a major part in DQM, for they are in charge of the overall environment of the architecture, systems, databases, etc. Once problems are recognized and everyone’s on board, standards can be set. If you’re goal is to have a perfect database, you’ve set your expectations too high. We must all realize there is no such thing as a perfect, “spot-less” database. Data quality is a balance between accuracy and completeness. It is impossible to have data that is 100% accurate and 100% complete. We often find that we must sacrifice one or the other. Depending on the data’s value, one can make the decision to keep a record with an error or toss it.

Managing data quality is a continuous process that needs to be re-visited frequently. It is important to update your data in a real-time fashion. If you’re worried about the costs of managing your data, you shouldn’t be. Quality is free; it is the “unquality” that costs money.