Data Integration Blog

With the financial crisis, mass lay-offs and vanishing resources, companies get only more demanding. We emphasize reliability and get only more irritated if things are not neat, simple and under control.

Software is the last thing you want to sweat about in this situation. So when your business depends on commercial software and it lets you down, things can really suck.

It’s interesting to watch how financial crisis makes a lot of companies previously skeptical of open source and software as a service turn to these two and try to get the most of them.

Open source looks appealing because it’s free for the most part and, you literally have a 24/7 support from a community of extremely committed developers.

SaaS is good because most of the work is already done for you, and subscription-based payment plans tend to be tempting.

Let’s go further though, to the pre-built solutions. These are even better, as they rid you of all manual coding and let anyone (Literally. Anyone.) on the staff “watch and relax”, making minimum to no effort at all.

Open source is free and out there available to everyone. You’re not making a long-term financial commitment by trying it. Neither are you sweating it while getting your bearings in a new pre-built technology. Work’s done for you. So, it’s like there’s a bonus that comes with a pie: not only are you saving money, you’re saving loads of time and increasing the overall efficiency.

Pre-built open source, the new green (pink, red… whatever), is it?

Software as a Service…a concept that seems so attractive and luring. Yet you can’t but ignore how some companies are constantly criticizing it, telling the “horror stories” of how “friends of their friends” wasted time and resources depending on their SaaS providers, how it’s totally unreliable to let your customer data out and let some outsider be in control of it.

Rumours and fears like that don’t come out of nowhere, obviously. Companies, especially small and mid-sized businesses, get very touchy when it comes to their data and security for a reason. And the reason is…being way too conservative.

In fact the ones that complain the most are usually the ones that realize the least just how vulnerable their data/software is inside their own company. Look at the real picture. With SaaS you’re not just letting out-of-house players be in control of your precious resources, but rather letting the pros protect, even fix it.

There’s nothing wrong with not knowing how EVERYTHING works and how to fix EVERYTHING. There are enough SaaS services to take a large chunk of your “everything” off of your shoulders. =) Then you’ll be able to focus on your internal assets and get double the work done with the same effort.

Let me list a few more benefits of having SaaS in your life:

* increased implementation speed;
* increased flexibility and usability;
* reduced dependence on IT services,
* access fom anywhere
* costs usually smaller than software license costs
* superior protection and security of your data

With that said…being conservative sure helps…sometimes… but as my coach used to say, “there's nothing wrong with being PROgressive”.

CleanUp! You first hear these words as a kid from your parents. Clean Up! When you hear this you usually know you’ve made a mess. Clean Up! This is what you shouldn’t be hearing, or, for that matter, thinking, in regards to your company’s data. Or, at least, if the prospect ever crosses your mind, it shouldn’t look as nasty and unpleasant as it used to in your childhood. =)

But nonetheless, clean up you should. If your source systems and the customer leads are a mess, of course. The obsession with clean data is only justified in this world of Business Intelligence, where looking at the picture as a whole and thinking big is not an encouraged, yet infrequent practice anymore, but a requirement.

One of the key elements to having your data clean and having a global view of your organization’s lifecycle is data migration. Wise data migration with an appropriate strategy and the right tools, not the sort where you splash money and remain in the same spot you started.

So how do successful companies approach this process? Simple, really. After you're solid in your decision to move you data, determine exactly what you're migrating and what it'll take. That is, identify the time, costs and human efforts that might be associated with this. It also helps to reherse. Unfortunately, not all integration vendors offer quality simulation/visualization tools, but that''s not too hard to fix.

Moving data around like that can also become a great opportunity to improve your data quality. That is, by checking its accuracy and consistency before sending it on to the new system.

Data quality problems cost U.S. businesses more than $600 billion a year, according to The Data Warehousing Institute. (14 Dec 2007)

How does that happen? How come companies are losing this much money and not even realizing there's a way to save up?

Again, the major problem usually lies in the source the data is received from and the way it is processed (if processed at all) before it enters the database/warehouse. Then there's also the currency of data, its accuracy, completeness, relevance and consistency.

When dealing with leads, a few of these problems can be avoided by using Online Lead Generation (OLG) techniques instead of buying from a big data provider with huge outdated databases. A recent Christopher Petix's article titled Marketers Should Avoid 'Dirty Data' discusses the major benefits of OLG as opposed to buying from data providers. Here are a few I thought really make OLG technique stand out:

- collecting new data for every campaign
- ability to set parameters for data collection
- consumers fill out information related to their demographics AND specify their interest in a specific product or service
- strict data cleansing processes, double-filtering

All of the above ensure a hugher degree of relevance, and, as a result, really help you save the money you'd waste otherwise on reaching out irrelevant leads.

So called "dirty data" not only wastes contact center agents' time, it also wastes a marketer's budget--and optimizing budgets is crucial in the current market conditions.

That's where you realize that data quality could be taken care of in advance, but you're stuck with your dirty data and need to deal with it (and consequently spend more).

Data quality has the ability to save marketers a considerable amount of money and is a completely transparent process.

What could be simpler?

With the speed on-demand solutions appear and gain popularity and compete with the old-school desktop systems, you'd naturally think customer data integration solutions have long become a usual thing. That's why it's a bit shocking to see the recent Forrester Research report only 2% of companies surveyed manage to achieve an integrated view of a customer data, while 92% claim this approach to be either "critical" or "very important".

Turns out, building bridges between web and desktop is still a problem, and we're only left guessing whether it's the loss of data, resources, or time that the companies are scared of.

But then there are enough pre-built solutions out there that won't take months or weeks of your time, and that you can use and be sure that nothing gets lost. Everything is simple, couldn't get more simple, in fact. Then why make it sound so compicated and scarry?

Just know what you need out of your CDI solution, and find one that would fit your requirements. Also, it helps to actually know what customer data integration is and enlightening your staff as to why the company need it. In this context, Jill Dyché's seven tips to get companies ready for successful customer data integration implementation might be useful.