Why big companies disappoint customers every dayAnd the three missteps stopping them from being customer-ready

customer ready.

Smart companies treat their customers in some pretty bad ways.

Smart companies treat their customers in some pretty bad ways.

Their marketers make product recommendations so irrelevant they feel like spam.

Smart companies treat their customers in some pretty bad ways.

Their marketers make product recommendations so irrelevant they feel like spam.

Their salespeople go into meetings with customers when they don’t even know how much the customers have already spent with them.

Smart companies treat their customers in some pretty bad ways.

Their marketers make product recommendations so irrelevant they feel like spam.

Their salespeople go into meetings with customers when they don’t even know how much the customers have already spent with them.

Their customer service agents irritate customers by asking them questions they’ve answered three times over.

We’re all customers. We’ve all experienced it over and over and over…

So why do smart companies make so many terrible mistakes?

We’re all customers. We’ve all experienced it over and over and over…

You could say no one in the enterprise actually cares about fixing these problems – but that’s rarely true.

You could say the exponential growth of applications and channels and teams makes even the simplest things impossible to do.

That’s probably true but doesn’t explain everything.

The real root cause is actually one level deeper.

The real reason even the best-intentioned, smartest companies do so many disappointing things is because their data isn’t customer-ready.

It’s a fragmented, siloed, inconsistent, out-of-date, error-filled mess.

It’s a fragmented, siloed, inconsistent, out-of-date, error-filled mess.

The result of this mess is that the smartest people can’t access enough data about customer relationships to give customers the experiences they deserve.

It’s a fragmented, siloed, inconsistent, out-of-date, error-filled mess.

The result of this mess is that the smartest people can’t access enough data about customer relationships to give customers the experiences they deserve.

Without great data, great customer experiences are the exception – not the rule.

So how do companies try to solve the customer experience problem?Let’s look at three missteps that most enterprises make – and why they fall short of solving the real problem.

1Misstep 1

Throw more applications at the problem

Misstep 1Throw more applications at the problem

There are some amazing applications out there. Literally hundreds of them, across dozens of categories from hundreds of vendors. But if the data fuelling them isn’t managed intelligently, they simply can’t deliver on their promise.

When you treat data management like the strategic business process it is, you give every customer-facing application and person what they crave: clean, safe, and connected customer data.

Great data they can base their decisions and actions on. 1

2Misstep 2

Trying to manage the data manually

2Misstep 2Trying to manage the data manually

Before sensor data and streaming data and social data – before big data – managing data was a lot simpler. Now it’s crashing in from all directions and being used everywhere. So trying to manually clean and integrate it is a thankless, time-consuming process that ends up out of date and filled with errors almost immediately.

2Misstep 2Trying to manage the data manually

Fix your data in one place and the issues peppered across the rest of the organization remain.

With small datasets, merging every spreadsheet and cleaning every cell may be feasible, but the bigger and more diverse the data, the harder it gets. You don’t want to do this manually.

3Misstep 3

Fixing the data once

3Misstep 3Fixing the data once

Data quality erodes at a rate of 27 percent every year. Customers change jobs. They change addresses. They change preferences.

So even if you manually cleaned and connected and related all your data in one go, the amount of new data you’d need to put through the same processes makes a mockery of your efforts.

3How much new data are we talking about? A lot. The average B2B organization doubles its prospect and customer data every 12-18 months.

Intelligent data management never stops. It’s a constant cycle of connecting, cleaning, mastering and relating the data – then publishing it back to the customer-facing apps and people who need it most.

Misstep 3Fixing the data once

Get it right and your customer experiences can be all they ought to be: informed, timely, relevant, compelling, and personal.

Get it wrong and the shiniest apps in the world can’t help you do smarter things.

The bottom line:being customer ready means having great data in the right apps at the right time.

It means knowing all the little things that make a big difference:

It means knowing all the little things that make a big difference:

That the Jakki who bought those shoes online is the same as the Jacqueline returning them in-store.

It means knowing all the little things that make a big difference:

That the Jakki who bought those shoes online is the same as the Jacqueline returning them in-store.

That the company your B2B sales team is pitching to is full of customers of your consumer products.

It means knowing all the little things that make a big difference:

That the Jakki who bought those shoes online is the same as the Jacqueline returning them in-store.

That the company your B2B sales team is pitching to is full of customers of your consumer products.

That the recipient of your happy, chirpy marketing email is currently screaming at customer service.

It means knowing all the little things that make a big difference:

That the Jakki who bought those shoes online is the same as the Jacqueline returning them in-store.

That the company your B2B sales team is pitching to is full of customers of your consumer products.

That the recipient of your happy, chirpy marketing email is currently screaming at customer service.

That George is a loyal customer in London but gets treated like a brand new one in New York.

It means knowing all the little things that make a big difference:

That the Jakki who bought those shoes online is the same as the Jacqueline returning them in-store.

That the company your B2B sales team is pitching to is full of customers of your consumer products.

That the recipient of your happy, chirpy marketing email is currently screaming at customer service.

That George is a loyal customer in London but gets treated like a brand new one in New York.

That Charlotte just bought a new TV so she shouldn’t be shown offers for more TVs.

It means giving your smartest people the data they need to make smarter decisions.

For smart companies to make sure they’re being smart about the way they treat their customers, they need to have a clean, consistent, and connected view of the total customer relationship.

We’re so into this stuff we’ve written an eBook all about what it takes to make your data customer ready.

If your smart company treats your customers in not-so-smart ways, you’re going to like this eBook. A lot.

Download it now.

About InformaticaWe’re Informatica and we’re empowering enterprises bold enough to develop the new data organization. We do this by helping them build modern data architectures that turn data management into a strategic discipline that uncovers insight and confers advantage.

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