Data Analysts are a Marketer’s Best Friend

Marketers today need to be comfortable with data. They need to be able to understand what the data is telling them and how to make decisions based on that. The best hunches or instincts in the world cannot compete with data-driven strategies. Not in 2019.

But you and I are not the experts. We didn’t go to school to learn how to work with data (though perhaps more marketing coursework in the future will involve data analytics and statistics).

That’s why we need to befriend the people who are experts.

Data analysts and data scientists are the folks who know how to make sure your company is collecting the right data, how to review and sort through that data to get answers to critical business questions, and how to present their findings in a way that makes it easy to make business decisions.

For marketers, this skill set is a godsend. Here are just a few of the key ways marketers can work with data analysts to achieve better business results:

  1. Build real-time reporting by advertising channel that lets you view return on investment at the high level across channels and dive deeper within each channel to improve optimization decisions

  2. Gain a deeper understanding of how customers are progressing through the buyer journey and identify opportunities within the sales funnel to improve the likelihood of conversion

  3. Build more robust buyer personas with first-party data collected by your company that will help your sales team prospect more effectively and influence future branding and messaging decisions

  4. Isolate the impact of key pricing and promotional campaigns in order to determine the ideal pricing strategy that drives maximum profitability and sales

  5. Connect your data with key advertising platforms to derive greater value from AI and machine learning going forward, letting algorithms take the lead of spending decisions in order to maximize efficiency

Every marketing organization today needs people who are fully engaged with the data their company and their customers are generating. This data is a treasure trove of information that can be used to guide decisions at every level of the company.

As a marketer, you would be smart to spend more time with your company’s data analysts and data scientists, leveraging their incredible skill set to help you do more.

What Are Your Key Performance Indicators?

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How do you know if your business is doing what it is supposed to do? How do you know if you are doing well or not?

Sounds like an easy question to answer, doesn’t it. But for too many companies, it is not so black and white.

But it should be.

What Are Key Performance Indicators?

Key Performance Indicators (or KPIs) are the business-defining metrics that you will use to answer the questions posed above. And the only person that can tell you what those KPIs are, is you.

Each industry and each company might have different ones. You might have just one of you might have five. They might be focused solely on revenue or they might be focused on new customers.

Not Just Any Metric

The key is in the name – Key Performance Indicator. This is not just any metric. This is the one that gets right to the heart of success. If the metric is positive, you are doing well. If not, you have work to do.

A good test to decide whether a metric is truly a KPI is to think about a situation where said metric was moving in the right direction, and yet the company itself is moving in the wrong direction.

For example, let’s say you choose a new customer metric. Is it possible that you could be seeing strong growth in new customers, but at the same time see shrinking revenue? If so, than new customers alone is not a great KPI.

Can You Have Too Many KPIs?

Yes. Most businesses will have more than one. But it is important to limit it to as few as possible.

Why? Because the more metrics you have to look at to determine the overall health of your company, the more difficult it becomes. They don’t have to tell you what’s wrong when things are wrong, that’s what analysis is for.

A good rule of thumb is to keep it to 5 or fewer.

In Conclusion

KPIs are the metrics that you use to answer the question, “how is the business doing?” They should be readily available and easy to understand and explain.

Measure WHEN Your Sales Happen

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Ecommerce companies that have grown smarter about data and analytics are starting to ask themselves questions that they may never have asked before. We are asking questions about how our users are interacting with our websites. We are asking questions about what marketing campaigns or special offers lead more people to purchase. We are asking questions about what elements of our website are preventing people from converting into paying customers.

But there is a question you are not asking, or have not asked yet, that could be just as important-

When do people buy from us?

In retail, or any type of business with a physical presence, it makes more sense. We want to know when our store is busy, so we can make sure to staff the right amount of people. And we might even run special offers to try to get people in the store during down times.

But online, the question might at first seem counter-intuitive. Online stores are open all the time. There is no staff required. People can buy when it’s convenient for them, so why do we care?

But the answers to that question are actually quite simple. By knowing when people buy, we can optimize our marketing efforts in the following ways:

  1. Send out special offer emails on days and during hours that are more likely to lead to conversions
  2. Make sure your live chat and phone support personnel are available during the busiest hours
  3. Utilize promotional banners and offers on the website to increase sales during times when purchases typically are lower
  4. Run your advertising campaigns during hours when they are most likely to have the desired impact
  5. Run disruptive tests or website/server updates during times when there is less risk to sales

Ethical Questions for Marketers – Part 1

Welcome to the newest installment of our weekly blog series, Ethical Questions for Marketers. Each week we plan to introduce a new topic and explore it in detail, preparing marketers for the day when they face such a problem at their organization.

This week’s topic: Customer Privacy

Privacy is a subject that is all over the news these days. Usually, that news focuses on one specific form of privacy – cell phones, government surveillance, consumer rights, etc.

For companies, and marketers more specifically, the big concern is customer data. While today’s digital landscape makes it very easy for businesses to collect and store massive amounts of information about its customers, the ethical questions rarely get the attention they deserve.

Should we be storing such data? How much data do we need? What data is deemed too sensitive to store?

The risks with storing such data is that it can be used in ways against our customers’ interests. Even assuming for a second that your company would never take advantage of customer data (which is more than can be said for many companies), hacks and accidental leaks are inevitable. And so what happens when your customer data finds its way into someone else’s hands?

It is important for marketers to ask these questions internally, and stand up for the rights of your customers, because we are the managers of our brands. Brands that will certainly suffer as soon as private customer data gets exposed.

We need to be sure that the companies we work for are taking steps to keep information limited, confidential, and secure. While data helps marketers do their job, it’s better to have less of it than to risk its exposure.

Stay tuned next week for another installment of our Ethical Questions for Marketers series. If you have an ethical topic you’d like to see addressed, write us.

Don’t Blindly Trust the Data

The business world is obsessed with data, and for good reason. New technologies allow us to collect and analyze huge swaths of data. And the smartest companies out there use that data to find actionable insights, things they can use to help improve efficiency and grow the company.

But in order to make sense out of the data, human beings need to get involved – to dissect, analyze, and draw conclusions. And that’s where things can go wrong.

Don’t blindly trust the data. We need to learn how and when to question it in order to get the most from it.

Sometimes the data will suggest something that common sense will tell you is wrong. Sometimes one metric may look good while competing metrics do not. Sometimes a problem you thought you had turns out to not be a problem at all.

What can go wrong?

  1. The sample size may be too small. You can’t draw real conclusions unless you have a statistically significant result. When the sample size is too small, one data point can have an overwhelming effect one way or the other.
  2. The analyst incorporated his or her own bias. It’s easy to mold any dataset to fit some preconceived belief. The data should guide the theories and not the other way around.
  3. You may be asking the wrong questions. When you start with a question, you look at the data that you think answers that question. And you might ignore a more important data set that you otherwise would have looked at with a more appropriate question.
  4. The visualizations used don’t tell the full story. There are a great many common mistakes people make when trying to tell a story with visualizations. Charts and graphs can be distorted to over- or under-sell a specific story.
  5. Confusing correlation and causation. Just because the data shows you that two things are true about a certain population, doesn’t mean that one thing causes the other.

These are just a few common things that can go wrong when companies try to draw actionable insights from the data available to them. By learning more about how to work with data, managers and decision makers can prepare to question the data that they’re getting, rather than blindly following the recommendations by their data scientists and analysts.

The key is to know what can go wrong, that way you can avoid it.