Data Strategies

Destroy the competition with these data strategies

In the movie Moneyball, Peter Brand fundamentally changes the way baseball players are scouted and evaluated.  
 
Statistics in baseball aren’t new, in fact baseball is arguably one of the most numbers-oriented sports in existence.  From RBIs and ERAs to batting averages and at-bats, there are hundreds of metrics that have been tracked regularly in baseball since before Peter Brand was born.
 
But it took Peter Brand for baseball to start using data as a competitive advantage.
 
So where do you get started?  It clearly works for baseball, but you have to deal with privacy issues like HIIPA and PCI.  Baseball may be business, but business isn’t baseball!
 
It’s time to move beyond historical reporting and forecasting.  Let’s talk about some ideas to get you started using your data as a competitive advantage.  

The traditional way

Before we jump into new ideas let’s address a couple of traditional methods that should be in your portfolio.

Increase existing revenue

One common use of the historical reporting you do today is to identify behaviors that have worked in the past and repeat them.  Did the sales of orange swimsuits increase this time last year?  Order more.  Has revenue from the southwest region declined year-over-year?  Dig into it and figure out why.
 
Most of you have these processes in place already, so we won’t focus on them here.  But it’s baseline functionality.  If you’re not measuring your performance, this is the place to start.

Decrease existing costs

Likewise, reducing current spend systemically by measuring performance and taking action is a foundational piece of any data strategy.  
 
You can further break this into two rough categories:
 
Finding anomalies.  Does one manager spend more money to achieve the same results?  Find out why.  Does one employee spend far more on business expenses than someone else in the same role? Could be a problem.

Elimination of costs. Technology changes rapidly, and many jobs that used to be commonplace are disappearing.  While eliminating an entire job isn’t that common, pieces of jobs are automated all the time. Do you have someone checking paper levels in the copiers?  That can be automated, or the frequency reduced by measuring paper levels automatically.  Are routine customer inquiries handled in a call center?  Move them to an FAQ or automated response line.  Data is the key to finding these opportunities.
 
Chances are you’re doing much of this already, but it’s the first place to look before casting a wider net.  
 
Whether you’re reducing costs or increasing existing revenue, any money flowing through to the bottom line allows your business to be more flexible.  Opening up financial options gives you many more competitive options.

New revenue streams

Now that the basics are out of the way, let’s look at other ways to use your data.  
 
This is the point where many people say, “wait a minute!  I can’t use my data to create new revenue...we’re limited by regulation, compliance, or privacy laws.”  
 
And that’s a good point.  But you still have options.

Target the market

If you aggregate your data to a much higher level, many of these concerns disappear.  Information about what I’ve purchased in the past 30 days has clear privacy implications.  Aggregated information about total retail spend of the past 30 days at a national level is a different story—it tells us nothing about an individual.
 
But it could be very valuable to someone trying to predict changes in the consumer price index.
 
What industry are you in?  What metrics does your industry use to measure performance, or report to a larger audience?  Can your aggregated data be a predictor of an economic metric like CPI?
 
One word of caution—be careful about anonymized data.  Aggregated data can’t be tied to an individual as long as there are enough data points in the groupings, but just changing personally identifiable information in a record isn’t enough to truly hide the origin.  We’re talking about aggregation here, not anonymization.

Target your customers

Even if your data is extremely sensitive,  there’s usually one audience that can see it without concern:  the people who generated the data.
 
Do your customers have access to the data you generate from their behavior?  
 
In some industries, they do have access—but it’s generally via static, pre-defined reports generated on a periodic basis.  What if you gave them more interactive access to data?  You might even be able to charge extra for that capability.  But even if you don’t, it would be a huge competitive differentiator.
 
Here are some industry-specific examples:
 

  • Healthcare: Do your patients or customers have online, ad-hoc access to their health records, or their insurance benefits?  How could you improve that access?  What information about that data would be valuable to them, like spending trends over time, or a risk analysis that allows them to improve behaviors which may result in lower premiums or better outcomes?
  • Retail: Loyalty cards are everywhere. Do your customers have access to their spending patterns?  Are your vendors able to analyze stock levels or product performance in real time?  Both could provide value to the right audience and differentiate you from your competition.
  • Financial Services: This industry is often an early adopter, and online trading and banking platforms are more robust than they’ve ever been.  Your customers can almost certainly access their transaction detail, but how much analytics do you provide?  Do you give them the tools to slice and dice by categories, and forecast balances and expenditures?  Automatically identify outliers? Any of these would make your platform more sticky, and your product more competitive.

Microsegmentation

The marketing department has historically been one of the most avid consumers of data, so it’s not surprising that they’d benefit from advances in the availability of data.
 
Segmentation has historically been done around a number of small groups, identified by persona or by clusters of customers identified using advanced analytics.  
 
By combining attribute-rich transaction data with real-time systems, we’re able to identify very small segments of customers—sometimes down to the individual level.  
 
Micro-targeted ad buys are one way to capitalize on this and increase existing revenue, but by focusing on the customer experience you have the opportunity to significantly differentiate your product from the competition.
 
Relevant content isn’t limited to ads.  How would the content you show customers change if you knew more about them when they’re engaged with your product or location?

A/B testing

You’re probably already engaged in A/B testing, offering two (or more) test groups alternatives and testing which is more effective.  If you’re not, you should start.
 
And if you are, chances are you should do more.
 
Netflix, Facebook, and many other data-driven companies are very good at this.  Especially when it’s combined with microsegmentation (above), you’ll make your product more engaging and drive the right outcomes.
 

  • Which online shopping cart experience results in the lowest number of drop-outs?
  • Which last-minute offers result in the highest average ticket price?
  • Which customer homescreen results in the longest engagement?
  • Which offer results in the most conversions, or most profitable customers?

 
Remember that this isn’t all about directly increasing revenue, it’s also about driving engagement, customer satisfaction, and ultimately using your data to compete more effectively.

Measurement is hard

This all sounds great, but in practice measuring the success of any changes can be hard.  Data is often a contributing factor to success or failure, not a direct cause.
 
One potential way to measure success is to identify secondary actions that are influenced by data, which may themselves influence positive outcomes.
 
For example, if you can’t tie more focused segmentation directly to profitability because many other factors changed at the same time, measure a secondary factor like engagement time, or customer satisfaction surveys.  While these may not provide direct linkages to positive financial outcomes, there’s likely to be a strong correlation.
 
Be patient as you implement changes, revenue and profitability will follow.

How are you using data as a competitive differentiator?

Let us know in the comments.

 

 

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