Point-of-Sale (POS) systems are continuing to evolve. What was once only a "processing and recording of sales" mechanism (such as a cash register), POS implementation is now a considerable competitive advantage in a retailer's strategy. As a result, retailers are always looking to get more long-term ROI out of their POS systems. They are determining how this interaction opportunity with a customer can support other parts of a company's multichannel sales strategy as well.
The operation of these systems is rapidly moving from a counter-based cash register to the retailer's floor, as credit card processing hardware increasingly supports this model. Mobile handheld devices, tablets and other consumer devices performing the actual sales transaction are now commonplace within a store, no longer tying personnel to the cash register. As a result, customers are now often asked to enter their own information via the on-the-floor transaction device, and an email address now more than ever is part of the collected customer information. Primarily, this is because customers increasingly prefer more efficient and environment-friendly e-receipts. Better yet, collecting an email address can then provide an opportunity for future communications via email for the retailer, and can result in increased ongoing customer engagement.
The value of collecting an email address can be considerable. Email-oriented and Web-based marketing are outpacing traditional advertising and direct mail methods, and multi-channel sales strategies are as critical to success as ever. Even with retailers where traditional methods of POS still make the most sense via a cash register, collecting email addresses are equally important for customer retention success.
However, there are a couple of challenges to collecting this kind of customer data on the floor. First, data entry can sometimes be a little tougher with these mobile devices. If the customer enters their own data, which is now often the case, the chances of collecting incorrect or invalid email addresses either by accident or otherwise can go up considerably. Even if the email address is collected properly, 30-40% of people change their email address every year. Simple typos or not, these issues can not only prevent e-mail receipts from being delivered, but a large incidence of invalid emails being entered can result in future marketing communications going into spam folders if Internet Service Providers (ISPs) detect enough email bounces and failed deliveries coming from the same sending source.
Real-time email validation that utilize an instantaneous out-to-the-Cloud check to ensure email deliverability can substantially reduce typos and otherwise bad email addresses from getting into the system in the first place, right there on the floor at the point of data capture. Utilizing this kind of technology of email address validation can reduce email bounces and failures by 90% or more. It can be an effective tool in ensuring the highest possible levels of data integrity when capturing customer details.
StrikeIron's Email Verification Solution is cloud-based; allowing it to determine in real-time if an email address is valid and deliverable before sending a message. It is used in many production POS systems today to ensure as often as possible that correct email addresses are obtained when collecting customer information.
The cloud-based, real-time approach is an important one, as StrikeIron is constantly evolving its algorithms in the background without requiring customers to update their POS integration in any way. Our team of email verification experts is constantly tweaking, enhancing, and otherwise modifying the algorithms that make these real-time checks as accurate as possible on an ongoing basis without any effort from the customer leveraging the technology.
Email Verification is only one easy-to-integrate API product available from StrikeIron. Others include Phone Number Validation, Address Verification, Do Not Call List checking, SMS Text Messaging and several more. For more information, please contact firstname.lastname@example.org.
There are many different kinds of batch data cleansing processes that can be performed against large databases of existing customer information. Standardizing inconsistent data, removing duplicate records, validating columns against up-to-date reference data, filling in missing data, and appending new data to existing data are all examples of customer data processing that can help improve the value of internal data assets.
When data assets undergo these kinds of processes their value increases and they enable business intelligence applications to be more useful, operations to be more efficient, and customer communication efforts to be more effective. These are worthwhile endeavors indeed.
However, it can often be a considerable effort to do large, after-the-fact database cleanup jobs - not to mention the considerable costs and complexity associated with offline data processing. Also, batch jobs are rarely a one-time effort, as the same problems begin to appear soon after a mass cleansing, and then begin to build to troublesome levels again, putting the data stewards of the organization back to square one.
An alternative can be to leverage real-time data quality mechanisms at the point of data collection
. This means validating data, filling in missing data, appending data, standardizing data, and comparing it to existing data for duplicates in real-time, before
it ever gets into the database. This can eliminate or dramatically reduce the cost and effort associated with downstream batch cleanup processes, enabling the benefits of clean, complete, accurate data to appear immediately across the organization. It also prevents the build up of these kinds of data quality issues over time.
Real-time data quality can be achieved by integrating calls to data quality functions
within business processes, Website data collection forms, customer-facing applications, call center applications where representatives speak with customers, and anywhere else that data is collected in real-time. Typically these programmatic calls are to Cloud-based APIs that are leveraging constantly refreshed reference data to ensure the highest possible data accuracy.
Here more than ever, an ounce of prevention is worth a pound of cure.
As you think about improving the quality of data within your organization, here are four quick and simple yet key tips that will assist in your approach and strategy on your way to success:- Think of data as a strategic asset.
Collecting and storing data alone is not enough. There must be a proactive plan in place to ensure that the data serving as the basis of decision-making, operations, and customer communication is treated as a strategic valuable asset. Effectively managing the quality, accuracy, and usability of this data on an ongoing, every day basis can translate into dramatic revenue opportunities and significant cost-saving efficiencies. - Consistency is as important as accuracy.
Accurate data is important, but so is consistency. Inconsistent representations of the same data content (such as variations of a company name, a lead source appearing six different ways, etc.) throughout data tables can make data very hard to analyze, and can even throw off analytics and business intelligence processes. This can result in decision-making (such as where to deploy marketing assets) based on faulty data points. A focus on data consistency can reduce the incidence of this substantially.- Data quality is far cheaper transactionally.
Improving the quality of data at the point of data collection (A Web form or via a call center representative) is much more inexpensive than waiting for broad data quality issues to appear downstream that must be addressed en masse. The cost difference can sometimes even be a factor of ten. Also, in the downstream case, considerable use of inaccurate and incomplete data might already have occurred. Validating the accuracy of data before
it ever gets into core customer databases is very important.- Data quality is about more than technology
Tools can only do so much. Incentive programs for capturing complete and accurate data (such as bonuses for 98% or greater accurate customer data point collection) can go a long way in better, more valuable organizational data, as well as education in the importance of data as a key strategic asset across business units, not just IT. Any comprehensive data quality plan built for success will involve the entire organization.
StrikeIron's partner ActivePrime will be leading a data quality discussion during a session at Oracle OpenWorld in San Francisco on Thursday, October 6th, at 1:30 pm PDT at the Intercontinental Hotel San Francisco, Grand Ballroom A.
One of the primary themes of the session are the differences in data quality for SAAS CRM solutions versus on-premise solutions, and how real-time data quality can be leveraged at the point of data collection. It will also focus on how to manage data quality in hybrid SAAS and on-premise environments. ActivePrime's Clint Bidlack and Rosaline Gulati will lead the presentation.
In collaboration with StrikeIron, ActivePrime's CleanVerify offering utilizes StrikeIron's Contact Record Validation Suite to provide a seamless real-time data quality solution within Oracle CRM On Demand. The SAAS solution leverages StrikeIron's Cloud-based data delivery capabilities to validate, correct, and enhance physical address data, email address data, and telephone data directly within the Oracle system.
Because all of the reference data is stored out on the Cloud, there is no need to ever perform reference data updates. Oracle CRM On Demand users can always rest assured that their data validation processes are always using the latest, most current data available as the basis for the ongoing validation checks.
Also in this session, ActivePrime will discuss case studies where they have delivered a much better data foundation to customers utilizing Oracle CRM On Demand in hybrid environments so they can maximize ROI and get the most out of their CRM and marketing processes. Customers Insperity (formerly Administaff) and Komori will be presenting about their experiences at the session. I will be in attendance and answering questions at the session as well.
2011 is the year social applications (Facebook, LinkedIn) are morphing together with location-based applications (Four Square, Google Earth/Maps, GoWalla) in new and exciting ways. As usage of these applications explodes, it is leading to new opportunities in the data space.
Smartphones (Android, iPhone) and tablets (iPad, Android also) are generating large volumes of location data as they are moved almost continuously from point to point. This data, combined with social and location applications, is creating a new wave of application innovation. The applications will be heavily dependent on a broad range of data however, not just user location data.
So where does StrikeIron fit in?
Much of the positional data behind location-based applications are generated by the devices themselves. However, much of this data is only useful when utilized in conjunction with large datasets of businesses, addresses, location databases, customer data and other types of relevant data that is being compared or referenced to. This can be especially valuable when delivered to a device providing some kind of valuable result or insight in real-time. However, it is very important that these datasets of reference information are accurate, comprehensive and current. Otherwise, the user experience can be quite frustrating and adoption of these applications will be slow and far less successful.
People and their organizations are gradually beginning to understand the importance of data quality in general, but for use with location-based applications, address quality is especially important.
StrikeIron's Address Verification capabilities are not only used to validate the existence of addresses, as well as ensure mail deliverability, but they are also used to generate latitude and longitude coordinates of an address as part of the validation process (as well as several different types of geocode data such as census tract data). These "geocodes" can then be used in many scenarios such as calculating distances between addresses or points from a certain business, legal uses of address proximity (many law firms use this service), real-time proximity to customers or prospects, geo-related business intelligence such as customer distribution, product distribution maps, satellite-related navigation, nearest store locators, assigning appropriate representatives in call center scenarios and many more. All of these can be enterprise or consumer-oriented in nature and each use case can be key components of social/mobile/location applications.
So as the proliferation of devices and more applications containing mobile, location and social aspects continues, technologies that ensure a high quality base of data for these applications to run on top of will be equally as important in this next wave of innovation. Fortunately, with real-time APIs from StrikeIron to insert anywhere in the process, it makes putting these new ideas to work a whole lot easier and effective.