StrikeIron Blog

Reducing the Total Cost of Leveraging External Data Sources

Making use of data sources available outside the organization can significantly improve both the efficiency and effectiveness of various processes within the organization. This is why almost every business utilizes outside data in some way.

For example:

* Showing prices in local currencies have shown to increase sales globally by as much as 25%. However, there needs to be a mechanism for keeping these exchange rates current as they can become out of date pretty quickly if they are not updated frequently enough. Sadly, I've seen organizations reload their currency tables in large ERP applications as little as once a year, and one can imagine how this approach can cause a tremendous accuracy problem. In other words, using external data sources correctly is just as important as using them at all.

* Verifying shipping addresses at the point of an e-commerce sale (or any sale actually)  utilizing postal reference data can prevent serious customer service problems.

* Building customer profiles of purchasers of a product or service using business demographic data sources can have a substantial impact on future marketing ROI.

* Using zip code and postal information data to pre-fill customer information forms in call center scenarios can significantly reduce per-call phone time for call center representatives, and enable more time for responsiveness to customer needs.

* Integrating state and local sales tax rates into e-commerce transactions can significantly reduce accounting efforts down the line.

These are just a few simple examples of how external data sources can be leveraged to improve business processes. However, what typically prevents outside data sources from being used as described above is the cost to acquire entire data sets, bring them in house, maintain and update them regularly, and of course the cost of the personnel to manage these things has to be factored in as well.

Now however, the traditional cost, effort and complexity of leveraging these data sources can be dramatically reduced by integrating into them over the Internet via a Web services API on a per-use basis with a simple XML-based SOAP or REST call. Because of this type of architecture, these data sources can be integrated directly into to any application or Website that makes use of this data. This approach also ensures that the data sources in use are always the most up-to-date sources available since the updating process is centralized by the providing organization, also eliminating data aging issues.

The concept of the Cloud provides the technology foundation for this to be a reality, and with a simple couple of lines of code, leveraging external data sources via API over the Web can be done by any organization, large or small.

The Value of Customer Data: Addressing Quality Early in the Data Life Cycle

Customer data is a corporate asset that has a value and if managed correctly can provide an organization with a sizable return. The challenge often becomes on how to measure the value of this electronic asset and quantify its internal rate of return. Imagine for a moment if we could increase customer retention considerably, increase per-customer value, and also increase the number of customers that we have in total? While different for each organization, calculating this kind of return can be a fun exercise to do, and I firmly believe one way to achieve these gains is through the customer data asset.

Now, we all know a company's success can often be determined from how well it manages its customer relationships. The raw material for managing these customer relationships exist in the form of an organization's customer data. In other words, accurate, comprehensive, and complete customer data can help considerably in achieving better customer relationships. After all, how well can you communicate with your customer base if you have poor data to do it with?

As an example, ongoing customer communication such as a newsletter can strengthen ties and loyalty, as well as keep customers informed of positive company developments that make them want to continue to be a customer. However, without having accurate and up-to-date information for this communication (such as accurate physical addresses and current email addresses), this is not possible to do effectively.

Also, simple post-order product delivery to the wrong place due to address typos can create considerable customer service problems. We have all experienced the pain of items not shipped correctly to us from an online vendor, and the maddening follow-up process which usually occurs in order to straighten things out. Simple data verification at the point of sale can help reduce the incidence of this drastically.

With better data, call center representatives can respond faster and more effectively to customers when they don't have to spend time correcting customer information. This of course helps them provide better service.

Amazingly, organizations have invested millions of dollars into sophisticated CRM systems such as Salesforce, NetSuite, Oracle, and others, and yet the overwhelming majority of these instances are still plagued by inaccurate, incomplete, and otherwise poor data quality that grinds away at the ROI potential of these kinds of systems.

While the analysts have broad ranges of the cost of poor data quality to an organization, depending on what all is included and the characteristics of the organization, the one thing they agree on is that the cost is large.

The good news is that on the customer data front, the key to better data is to perform validation and data enhancement at the point of data collection, whether it be from a Web form, a call center, a mailing response, or any other way customer information is collected. These days with XML-based customer data verification services available via simple integration over the Web, this is quite easy to achieve.

Sure, good customer data can be augmented with back office processing by utilizing additional data sources, but this typically is only successful if the originally-captured data is complete and accurate.

So while the bottom-line impact of poor customer data is not always a straight-forward calculation, trusting your intuition that better data equals better customer relationships, and addressing the issue of customer data quality early in the data life cycle can pay significant dividends.

Driving Factors of Cloud Computing Only Becoming More Emphatic

One thing that's clear as we pass the halfway point of 2010 is that the Cloud Computing movement is not only gaining momentum, but the usage trends of the Web that are driving Cloud Computing are only increasing in influence and contributing to its momentum at a faster pace than ever.

For example, Facebook's Chief Technical Officer reported last month that they were seeing as many as one million photos being served up per second through the entirety of their Web-based social application, and that they expect this to increase ten-fold over the next twelve months.

Also, how many of us watched some streaming World Cup soccer games over the past month as Spain proved supreme in South Africa? Or at least highlights on YouTube and various other video outlets? Currently, it is estimated that 50% of all Web traffic is video. That's not surprising, but with High Definition (HD) Web technology and the like emerging, video is expected to represent 90% of all traffic in just a few years. This is going to require bandwidth levels that were largely unthinkable years ago.

On another front, mobile infrastructure is not keeping pace with demand. Right now, some estimates have shown mobile infrastructure requirements growing at about 50% per year, while actual mobile network infrastructure capacity is only growing at 20% per year. This is going to be a real problem, and one of the reasons some mobile carriers such as AT&T have begun capping usage and introducing fees for premium levels of bandwidth that were standard issue up until now, and other carriers may likely follow suit. It's the only way to help curtail demand to meet capacity in their eyes.

So what does all of this mean?

One of the reasons we have Cloud Computing in the first place is that innovative Web companies such as Amazon and Google had to build out enough computing capacity to handle peak periods of Web traffic and activity, especially Amazon during its Christmas holiday crunch.

As a result, they found themselves not only experts at building out distributed computing capacity, load-balancing, and data synchronization, but also found that most of the time they had all sorts of computing power that they had invested in for peak periods "shelved" and not in use, far from cost-optimized. This led them to think of ways to monetize this excess capacity (servers and disk space lying around idle) and led to some of the early thinking and innovation around Web-based centralized computing. The same is true with Google and others with all of their excess Web computing power, as they looked for ways to monetize large, excess amounts of capacity and leverage their expertise at building out server farms and developing highly-distributed, yet high performing levels of computing.

This same necessity-is-the-mother-of-invention phenomenon is playing out now as Facebook develops new technology to serve up its millions of photos per second, and is spawning new data storage and retrieval technology such as the NoSQL paradigm shift, with new non-SQL and "not only" SQL architecture approaches such as Cassandra, BigTable, Neptune, Google Fusion Tables, and Dynamo that are more finely tuned to the needs of Web-scale Cloud Computing.

In parallel, the bandwidth demands of video and mobile infrastructure are seeding new innovation around capacity and distribution of bandwidth as well, including much more efficient and easier to implement elastic computing capabilities to handle these variable bandwidth demands as much of mobile's required computing requirements are moved to and answered via the Web (and this also makes SmartPhones ideal Cloud Computing clients, also pushing the paradigm).

While not only mind-boggling and exciting, these trends are the cornerstones of a revolution already in progress. All of this demand-driven innovation is only causing more and more build-out of the foundation from which the future Internet and "Cloud" will emerge. A few years from now, we will look back and see how the Web computing demands of today, whether from Facebook, Google, Twitter, or others, enabled a whole new generation of Web applications to emerge. And of course, huge amounts of data were gobbled up in the process, a lot of which will have come from StrikeIron's own data delivery innovation in the Cloud.

No doubt about it, the Cloud is a good place to be.