Stringent deadlines, shifting priorities, multiple initiatives and more business problems can be solved with stronger, cleaner, enriched data, letting companies achieve customer intelligence. Here’s how.
Our business partners come from different industries, but they face similar challenges when it comes to achieving customer intelligence.
Economic uncertainty and rapidly shifting consumer needs mean business teams require long-term solutions that can be implemented quickly. Those solutions need to be cost efficient and adaptable to future changes in the market changes.
Luckily, good data–which is clean, organized and enriched–is a sure-fire solution that checks all the boxes. As we always tell our partners, good data is the backbone of customer intelligence.
It opens up new revenue streams, helps brands reach new markets and reveals pathways to meaningful, targeted customer engagement.
Whether our partners serve the energy, retail, financial or insurance sectors, they face some major hurdles. Chances are, your business may be struggling with these very same challenges if you’re working to achieve customer intelligence. If so, rest assured, stronger data can help you overcome them.
1. “My company wants to tackle multiple initiatives at the same time, but we aren’t certain where to start.”
Businesses have to be ready to serve their customers and beat their competition on many different fronts if they want to succeed. Appealing to different types of customers (i.e. residential vs. commercial; lower income earners vs. high-capacity investors), or serving different regions means may require different supports. And those supports must function uniquely to achieve different outcomes. It’s no wonder business teams aren’t sure which area to tackle first.
Clean, organized, segmented customer data can illuminate answers. Data that’s functional (or, as we like to say, operationalized) can do all of the following:
- Reveal dominant regional or time patterns, such as frequency of store visits, high traffic hours, common user profiles, etc.
- Uncover customer preferences, like which social media platforms certain people like best, which methods of communication are most likely to yield engagement from different customers, which are their favorite products and more.
- Predict trends, as in, anticipate the customer journey, where data indicates ‘customers that do X also commonly do Y next, and then they do Z,’ and so on.
We’ve helped our partners compare historical data against current data (e.g., customer account payments). This allowed them to predict which of their customers most needed certain support programs in order to pay off overdue balances.
In this way, data sheds light on which business initiatives, customer segments or geographic regions should be prioritized for given initiatives and which aren’t as urgent.
2. “Business priorities shift frequently in today’s market. How can we get ahead of the changes (or even just keep up)?”
Shifting priorities is just simply part of running a business. Unfortunately, we can’t always anticipate sudden changes, like the coronavirus crisis, before they happen.
When the pandemic struck, every business had to pivot. Whether it was acquiring PPE to keep employees safe, adopting new online sales platforms, or directing customers through new traffic patterns, companies (including ours) experienced dramatic, sudden priority shifts.
Businesses that had strong, clean data fared better than those that didn’t. With good data, they could quickly answer questions such as: “How many employees need to go virtual tomorrow, and do they all have company laptops?” And, “Which stores are most heavily-trafficked? They will need new directional signage and plexiglass for cashiers first.”
Implementing fixes in the face of uncertainty was possible for the companies that had data-backed answers right at the fingertips.
3. “We’re up against stringent timelines. How can we expedite our processes?“
Deadlines are always looming. Delivery dates are constantly drawing near. Sometimes teams have to push timelines back (or pull a lot of all-nighters) to accommodate some unforeseen hiccup.
Human limitations, technology malfunctions, even extreme weather events can prevent assignments from being finished according to plan.
Yet functional data keeps projects on course. For companies eager to roll out a new product or service, we’ve seen great success when they have, at their disposal, predictive propensities on hand. Which is a fancy way of saying ‘data that shows which kinds of customers are most likely to buy this product first.’
For instance, Marketing teams can fritter away time experimenting with whether email, Facebook ads or mobile alert campaigns will actually work to yield high engagement rates. Or they can aggregate channel preference data into their customer segments ahead of campaign launch to save themselves weeks–even months–of testing time.
That’s because they already have information on hand that tells them which customers should receive emails and which should see ads in their social feeds or via text message.
These tactics, and others like it, can be applied to any industry to keep buyers moving along the journey.
4. “There’s a massive amount of data available. I’m overwhelmed!”
It’s true. There’s so much data these days that, oftentimes, business teams don’t know where to start in organizing, gathering or understanding what sort will bring them relevant insights.
Internally, teams gather all sorts of data that should be usable by all departments across the organization. But when it comes to sprinkling in third-party data to paint a better picture of who the company’s customers are, things can get complicated.
Everything from health, housing and education data is downloadable for free. Regional demographic data is typically free, too. You can purchase data on how much time people spend on social media platforms. Or how much money they spend on pet care. Or how frequently they drink coffee. And on and on.
Simply having that data doesn’t just bring about customer intelligence. It takes more strategic planning to decide what to actually do with it.
The information that’s useful to one company isn’t necessarily worthwhile for another. But even within one company, data that’s relevant to the Sales team may not be so useful for those operating the Customer Call Center. Or for the Billing department or the Marketing team.
Even so, company data should be coalesced so that it’s accessible by all. For instance, it may come in handy one day for a marketer to know that certain customers have hit financial hardship. That way the marketer knows not to target those people at that time about a costly new product.
That’s why targeted, specialized data is so important. Putting a purposeful framework around data provides specific answers to specific questions, leaving out the fluff. Being specific about the data you purchase also saves money, because data isn’t cheap.
5. “My company has limited data resources. We don’t know what to do with new data–we can barely manage the records we already keep.”
Not all organizations have the financial wherewithal to support maintaining data so that it’s usable by all departments–or future generations of employees. And few companies have someone on staff who has the expertise to buy, download and synthesize data so that teams can solve problems with it.
While costly CRMs and multi-person IT teams aren’t absolutely essential for every business type, clean, organized data is a must for companies looking to grow revenue.
If lack of supportive data infrastructure is preventing you from achieving customer intelligence, it may be time to hire an outside vendor. Teams like ours can perform data cleansing, help you establish effective recording and maintenance protocols, assist you in choosing third-party data, help you make sense of it and put you on the path to customer intelligence.
If your business is facing one or more of these hurdles, let’s talk. We’d love to chat with you about how to strengthen your data and help you build a Customer Intelligence backbone. (Did we mention the process only takes a few months?!)