Why Retailers Build Data-Enabled Finance Teams?

By 2021, insights or data-enabled companies will make up to $1.8 trillion annually. 
It’s incredible. And it’s all because data-enabled teams are customer-centric. 
Data-enabled teams dig internal and external data to find what customer experience factors make their customers happy. 

Then they improve on those factors to drive more customer satisfaction. In the end, their revenue skyrockets. 
Particularly, data-enabled retail finance teams use daily transactional data to make informed decisions that’ll improve your store network. 
As a retail company, your finance team gets transactional data from credit card transactions, customer order history, reservations, etc., and non-transactional data from other department in your organization.

Smart finance teams in retail companies use all this data to make capital decisions.  And information from these transactional data sources is usually more accurate than many other data collection methods like surveys.  

This is because they provide data about your shoppers’ spending behaviour in your store as opposed to surveys and other research processes that are at the mercy of your respondents' honesty and accuracy. 

And since 55% of human communication is non-verbal, the actions or activities of shoppers when transacting with your store leaves breadcrumbs of critical data that are relevant to making informed financial decisions. These customer transactional data points can enrich your finance team with the relevant knowledge they need to make decisions that grow revenue and cut expenses for your store. 

However, making the right capital decisions is just one of the many reasons why retailers build data-enabled driven teams. Here are five more reasons why retailers build data-enabled finance teams: 

1. Right budget allocation for omnichannel marketing 

98% of Americans switch between platforms on the same day. 

They go from websites to social networks, forums, and mobile apps, and back to websites again. They’re always on the move trying to achieve one goal or the other. 

This explains why 67% of shoppers use at least two channels to make purchases. 

No wonder omnichannel marketing has quickly become a favourite for retailers these past few years — giving them more influence over their customers’ buying journey. 

But everything looks great with omnichannel until you try to allocate budgets to platforms your target shoppers hang around.  

Your thoughts begin to look something like these: 

“How much should I put into influencer marketing?” 

Or more specifically: “How much should I pay influencer A vs influencer B?” 

“Should I approve more budget for Facebook Ads?” 

“How much impact do Instagram ads contribute to sales?” 

A data-enabled finance team will dig the multi-touch attribution data from their marketing team to determine what percentage of the budget to allocate to each channel. This multi-touch attribution data provides an in-depth analysis of how much of your spend on a specific channel impacts revenue. 

They’ll also look at marketing attribution data to see how much of their revenue is coming from the specific channels they’re spending money on. 

 

2. A process for regular success

A data-driven finance team has a process for making capital decisions that looks something like this: 

  1. Analyzing data to know how worthwhile a project is. 
  2. Comparing options 
  3. [Insert relevant capital decision-making process] 
  4. Making final decisions. 

A process like this fosters regular success. 

For example, your web development team is proposing a full website revamp costing $125,000; is it worth the cost? Or what can you do to reduce this cost without sacrificing quality? 

A data-enabled finance team knows there’s no need to sweat over these questions. They know the answer they seek is in data. And that’s their process: they get data, find answers, and allocate budgets accordingly.  

Some likely questions they can analyze from data are: 

“How much is our current site making?” 

“Any there any proofs that revamping the design will improve revenue? 

“What’s our new design and has it proven more effective for another store like ours before?” 

These questions and more will uncover the truth about whether your site revamp is worth $25,000 or not. 

Even more, data-enabled projects are 2.5 times less likely to fail. In other words, your team will make better capital decisions when they’re data-enabled; teams that use data are 1.7 times more productive than teams that don’t. 

Make it data-enabled in the above figure 

Once your finance team’s decision-making process begins with data, they become armed with the right knowledge to make the best financial decisions. 

3. Quick capital decisions

As explained above, being data-enabled means you’re working with a process; you begin your capital decision-making with data and move from there. 

And processes that are driven by data like this make decision-making faster. Organizational psychologist Nick Tasler says in an HBR piece: “The quickest, easiest, most effective way to eliminate judgment errors is by “consulting an Anti-You” before you make every decision.” 

Let’s say five of your employees qualify for work travel.  

Their travelling will equally impact your bottom-line regardless of who goes. But the level of bottom-line impact they can produce varies. So how do you decide which one should go?  

Instead of wasting time interviewing each of them, dig your data. A data-driven finance team would go to HR and discuss the performance of each employee.  

If your team is not convinced after talking to HR, get the files on the five employees. You’re looking for answers to questions like: 

  • Which employee is bringing in the best results for your organization? 
  • Are their results quantifiable? 
  • If so, how much? 

This way, you’re quicker in deciding which employee has the highest likelihood of impacting your bottom-line if they’re chosen. 

 

4. An improved customer experience

When your finance team spends money on the right channels, tools, campaigns, and platforms, the result is an improved experience that shoppers get with your store. 

With the right data, they can know the right technologies that’ll increase customer experience and invest in them.  

They can work with your company’s marketing data, for instance, to find out your customers’ feedback and complaints. 

And almost 50% of retail brands using marketing data say they see improved customer satisfaction. 

 

When analyzing marketing data, you should be looking for answers to questions like: 

  • What pages on your site do shoppers visit the most? 
  • Does improving those pages require hiring an external agency?   
  • If so, how much? 
  • Are shoppers asking for specific mobile apps or app features to ease their interactions with your store? 
  • Do you need to introduce fingerprint functions into your store? 
  • What’s the budget for all of these? 

Data-enabled finance teams find answers to questions like these and are able to fund projects appropriately. The result is that shoppers who visit your store would easily notice how much you “get” them.  

They begin to wonder how you’re able to give them the exact things they’re looking for. All of that creates a great shopping experience for them. And 67% of shoppers say they’ll pay more for a great experience.  

 

5. Get return shoppers (customer retention)

The customer experience boosters highlighted in #4 above are usually also some of the things that foster customer retention.  

As data-enabled teams invest or allocate marketing spend to improving their most visited pages, creating customer-centric mobile apps, etc., they also end up boosting customer retention.  

And return shoppers always come back to buy and boost your revenue. 

They can significantly boost your revenue; a mere 5% boost in customer retention has the potential to increase profits by 25% to 95%. 

 

Not only do return shoppers increase your profits by large amounts, but sometimes they also return with more customers.  

Essentially they do free marketing for your store.  

So, data-enabled finance teams look to data to see things that boost customer experience at their stores and continue to invest in them. The more they do that, customer experience improves and high customer retention rates follow; shoppers come back since they had a great experience in the past. 

So the more a finance team invests in whatever data says boosts their customer experience, the more return shoppers they get — which increases revenue by almost 100%. 

Overall, data-enabled retail finance teams make better capital decisions  

In the end, data-enabled finance teams in retail organizations maximally utilize data to make capital decisions that improve brand and shopping experience for consumers. 

And, as mentioned above, customer experience improvements lead to more revenue and drive return shoppers — leading to millions in revenue. Across the 18 U.S. industries examined in a study, the revenue increase ranges from $141 million for health plans to $382 million for fast food chains.  

In other words, every customer experience improvement drives more revenue in return. 
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