Why companies aren’t using unified data and BI in their marketing campaigns

One of the main issues your marketing department struggles with daily is measurement. How do you gather, measure, understand, and make good marketing decisions without access to reliable, verifiable data and insights?

It’s a common problem. Customer service, operations, sales, IT, and other departments are swamped with information. It’s difficult to merge all of this data to help make important marketing decisions. For example:

• Budget — How do you know where to spend a marketing budget most effectively?
• Channels — What are the most effective channels to reach and influence prospective customers?
• Customers — What’s the best way to segment and understand your audience?
• ROI — Where is your marketing spend making the biggest difference, contributing most to your bottom line?

The answers are in there somewhere. Big data analytics can help to bring together and unify all your company’s marketing data, allowing marketing leaders to base decisions on business intelligence and deep insight. So why aren’t more brands using this kind of unified approach, merging their data from various silos?

To get some answers, I spoke with John Loury, President of Cause and Effect Strategy, a marketing and analytics agency based in upstate New York. Loury is a firm believer that all marketing must be strategically linked to goals, ROI or business KPIs. His experience speaks to some of the key principles at play here, and how to overcome them to use data for real growth.

With the right data, your marketing team can make much smarter decisions regarding where, when, to whom and how to market products and services. This translates directly into higher revenue and better profits for your organization.

Here’s his take on how it all works.

The common challenges around merging data sources

The first thing to realize is that you can’t analyze and understand data in silos. You need a unified, centralized place to store and analyze all of your marketing data to make informed decisions.

“Today, most of the challenges we encounter are rooted in self-fulfilling prophecies or misconceptions of what is now possible with business intelligence and analytics,” he explains. His team hears a lot of excuses for not effectively merging the silos, things like: ‘We don’t have enough data to aggregate,’ or ‘Our sales and marketing departments don’t work well together, so they don’t share information.’”

There’s even some fear over automated BI will automate tasks and democratize data, which could impact job security and prestige. So getting buy-in and agreement across the organization is crucial.

Unifying and structuring complex datasets from diverse sources – and overcoming the human objections in the process – is one of Cause and Effect’s specialties. The goal is to create a way for even non-technical team members can perform their own analyses.

“We use Sisense BI because of its ability to easily merge diverse and siloed data sets that exist inside and outside of a company’s four walls,” he explains. “In some cases, we can connect in near real-time and aggregate data sources like Facebook, Salesforce, and Google Analytics that are siloed, along with data that’s stored internally like sales, accounting, homegrown CRM, etc.”

How can business intelligence help ferret this info out? “With almost every client we engage with, once we standardize a data flow there are always some inconsistencies that spark statements like ‘Oh yeah, this piece of data actually means this,’” Loury notes.

The process helps uncover these inconsistencies and brings transparency to bear, “but getting information that only exists within an individual employee is the most difficult part, and it’s tough to see that changing.”

Mining for insights

As a company begins to aggregate all the data, they can start to dive into the data, analyze it, and mine out the nuggets that drive business and marketing decisions.

At this point, it’s important to identify what kind of insights you’re looking for, and how it applies to marketing strategy. For example, your team might want to:

• Understand customer lifetime value — Use customer information to identify the types, categories, and demographics of customers and what they spend with your business over time. Identify your most profitable customers.
• Map out the customer journey — Learn the various touch points customers have with your business prior to making a purchase decision.
• Understand the most effective channels — Contrast and compare the various marketing channels used to reach customers, together with the conversion rates and average customer lifetime value of each.
• Identify return on investment — This is the holy grail of marketing metrics. Analyze where it’s most effective to spend budget to get the best conversion rates and revenue from your customers.

Loury sees the insights falling into two separate buckets: vertical specific, and stakeholder-specific.

“Virtually every client in the nonprofit fundraising vertical is interested in the insight buried in metrics such average gift, cost per dollar raised, lybunts/sybunts, and more,” he explains. “The second is more specific to the individual stakeholders that we work with and may relate to a specific initiative, marketing campaign or KPI.”

Retail organizations might use historical data to find insights into metrics like retention rate, acquisition rate, attrition rate, and average lifetime value.

“Once we combine these metrics with marketing data, our clients are able to realize insight related to channel attribution, audience segmentation, and true ROI,” Loury explains.

When it rains, sell umbrellas

There are, of course, elements of both art and science when it comes to turning insights into marketing strategies. Loury gives the example of a client who sells outdoor equipment. They suggested doing a historical analysis of sales by geography in relation to droughts and rainfall.

“By combining weather and sales information, we better understood the impact weather had on sales and were able to influence increased marketing spends across the areas impacted by weather to match customer demand,” he explains.

Because they can use data to gain greater visibility in their clients’ business, they enable them to make more intelligent marketing decisions, in less time. And that means more revenue and faster growth.

It then becomes possible to:

• Find and eliminate bottlenecks in the customer journey — Improve touch points, handoffs, and bottlenecks in your marketing, sales, and onboarding processes. Help your business better manage the customer journey and make it friction-free.
• Properly identify and segment your audience — Customize marketing campaigns to directly appeal to different types of customers and personas. Link spend on marketing campaigns back to the expected lifetime value of acquiring those customers.
• Split test channels, creative, approaches, and more — Test different marketing approaches to identify the strongest ways of reaching customers. Run multiple split tests to see what works for your audience.
• Understand return on investment — Bring all of the information together to fully identify and understand the right ways to spend on marketing campaigns to create the highest revenue and profits.

As your marketing department makes these improvements, you can continue to mine and query the data so you can be certain what decisions are driving what results.

Sound marketing investments

Spending some time and effort bringing together, analyzing, and understanding marketing data can have a huge impact on your business’s bottom line.

When you use that data to create actionable business intelligence, your marketing department can use those insights to spend their money more wisely, get a deeper understanding of their customers, and create compelling campaigns that win you more business. The business intelligence you have at your fingertips can create significant change throughout your organization.