Running A Data Driven Business: Using an analytics toolkit

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Using analytics can help you see a shift in your metrics, either positive or negative.

With proper analysis you can understand how to either exploit that positive opportunity or fix something negative that’s going wrong with your campaign or sales funnel initiatives.analyzing-data-3

  • Asking the right questions: finding discrepancies and questioning your data results.
  • Why has your average new orders dropped?
  • Why are you seeing less new visitors to your site this quarter?
  • Generating hypotheses: drawing a conclusion about your question that can be tested and evaluated.
  • Example: I’m driving less new visitors because I’m spending less on paid traffic.
  • Example: I’m driving less new visitors because my website is loading slowly.
  • Then, test and evaluate your hypothesis.
  • Contextualizing data: identifying and recognizing factors that could influence your data.
  • Example: I see a downward trend with my site visitors. What could possibly have changed?
  • Has something changed in my business? A competitor’s business?
  • Site changes and strategy changes: think about these before coming to a conclusion.
  • Data lies and it always will. But by contextualizing you’ll see the natural bumps and valleys and see the real trends in your information.
  • Testing and evaluating: reviewing drill down metrics and relevant information to prove or disprove hypothesis.
  • See if what you assume has happened.
  • Look at deeper dive metrics and see if the hypothesis makes sense. If so, what can you do to take advantage of what you learned.

Here at Up Automation, we have discussed the importance of using analytics to drive data-driven decisions. Analytic decision making is not just looking at raw data and deciding. It requires a flow of a thought process and proper analysis to ensure you are using data well.
Analytic Decision Making Flow Chart

Step 1: CHOOSE YOUR FUNNEL STAGE

  • This is the place where you want to be optimizing if you are…
  • Not driving new leads.
  • Not driving enough people to the middle and turning them into leads.
  • Not driving enough people to the bottom and converting them.
  • Decide where you want to take action and prove something.

Step 2: REVIEW KEY METRICS

  • Once you decide where to focus your efforts, review the metrics to let you know what is actually happening.
  • For example: if your average order value dropped 13% (at a time you expected more buys), this should tip you off that something is wrong or needs to be remedied
  • For example: Core offer conversion rate is down 5%, you know your business is underperforming.
  • You’ll often see the metrics in the same stage dip as something has changed.

Step 3: FORMULATE YOUR QUESTION

  • Think about what you are trying to figure out: What changes you are seeing in your key metrics so you can properly question them.
  • The question you chose to ask, sets the stage for the hypothesis you generate and ultimately tells you whether you’ll be able to test and improve your business with that testing. Just like 8th grade science class basics!

Step 4: CONTEXTUALIZE WITH THE ANALYST’S TOOLKIT

  • This is a series of questions to ask yourself, to help you look at the data:
  • What might be influencing the sale?
  • What might cause the avg. order value to drop?
  • Did we change a promotional strategy?
  • Are we spending less money on paid traffic?
  • Is this a buying trend that is happening historically? Externally? Internally?

Step 5: FORM A HYPOTHESIS

  • Take your question: what’s going on with the key metrics?
  • Take the context. For example: You know order value is down but you also know that traffic is NOT down.

Step 6: REVIEW DRILL DOWN METRICS

  • The KEY METRICS act as flags.
  • They indicate when you need to take a look at something. You’ve got a baseline and a key metric, and you see a big shift from what you are expecting to see, that’s the flag.
  • The drill down metrics are the tools to actually dig in and figure out what’s going on. Look at more minute things:
  • What kind of traffic is coming to the site?
  • What kind of actions are they taking?
  • Are they reading our new content?
  • Who is reading it? Who is interacting with it?
  • How is each individual funnel performing?

Step 7: PROVE OR DISPROVE HYPOTHESIS

    • It’s rare that your first hypothesis will be tested and shown to be the answer to your problems.

Often you’ll go back and form another hypothesis and test it. Check multiple hypotheses even if the first one was correct.

Step 8: APPLY INSIGHTS

  • Stick with the process: Look at the funnels, look at the metrics. Figure out what is wrong.
  • Apply what you find to improve your website, your customer experience.
  • Improve and build your business.

Use the Right Lens: an Analytics Toolkit

A huge mistake is to take a large collection of data and misapply your findings. In order to help analyze your data well, consider some of these analytic lenses through which to see your data.

Take your boring spreadsheets and turn them into stories by asking questions of what’s happening and what the different factors are that may be influencing or shaping what you’re seeing. This will give you the context that you need to analyze your data.

It’s important to note that data does not start out perfect. There will be inherent flaws in the numbers you are pulling. There’s no escaping this! Even if you follow every analytic process perfectly, you will not have perfect data.

The Toolkit

Decision making requires context. The toolkit gives you context:

Historical lens: Historical data looks back at existing data and uses that to shape what you are seeing right now.

Contextual lens:

  • Raw numbers v. percentages
  • If looking at new visitors to your site, compared to last year, and looking at raw numbers (total number of new visitors), you’ll likely say “wow!”
  • Then convert the raw number to a percentage: what percentage of visitors coming to my site is old vs. new? Number may dip.
  • DO: talk in terms of ratios to compare data sets of different sizes to get a better understanding of what’s going on.
  • Baselines skewed by outliers?
  • Remove the numbers that are dramatic or heavily weighted, even if true, to understand the general trends you see.
  • But—remember that the outliers exist to make changes as needed.
  • Data correctly pulled?
  • If number seems odd, pull it again. Likely it was manually input incorrectly

Transitioning From Reactive to Proactive Analysis

Regarding the Analyst’s Marketing Funnel, where each part of the funnel has its own metrics and separate goals, as you try to be a more proactive business, you need to leave behind the reactive strategies of these numbers telling you about this stage.

  • Start thinking holistically. That is, your business as a whole, a complete organism.
  • Where every part influences each other.
  • Every part is connected.
  • When something happens here, it influences everything that happens elsewhere.
  • Become Proactive
  • Understand the analyst’s funnel is connected: the analyst’s funnel, and all funnels, do not exist in a vacuum, all the parts work together.
  • From a visitor to a customer to a multi-buyer: all of these stages are connected.

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  • Start with goals, then reverse engineer: use your desired end result to map out what success looks like.
  • Work backwards to determine what to do at each different stage of the funnel.
  • It doesn’t need to be revenue-tied; it just needs to be something you believe to be accomplishable AND something you can reverse engineer back to reach that goal.
  • Track and optimize along the way: use your analyst skills to improve performance at every stage to hit and surpass your goals.
  • Don’t start with the optimizing and tracking. Start with a plan for what you want to accomplish.
  • Then figure out where to optimize, looking at the numbers you tracked and figure out how you can build your business.
  • Use your analyst skills at the END of the planning, at the END of the reverse engineering process, to improve performance at every stage.

A business without data cannot grow. But more importantly, not using the data well is just a waste of time and waste of resources. By using these tools and analytical lenses, you will be able to start making smart, informed, and effective decisions to get your business growing and successful.

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Measuring Money: Retention and Monetization Analytics

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In the past weeks, we’ve discussed a lot about monetizing your campaigns to help grow your ROI.

When we talk about success, we are referring to how many successful sales are made, and how many sustainable conversions were made. However, monetization is more than just about that first sale. analytics_graphly

The goal of monetization is twofold:
1) Sell existing customers more things.
2) Try to keep existing customers satisfied with your offers so they stay customers longer, keep buying from you, and don’t refund the product.

As you build your campaigns (whether social media or email campaigns) you will absolutely need to gather data in order to properly assess how successful they are.

Retention & Monetization Key Metrics:

  • Membership Retention Report: Is your membership program growing?
  • Traffic ROI Report: Are your ads achieving ROI or are they fatiguing?
  • Refund Report: Are your customers unhappy with your products?
  • Monetization funnel conversion rates: How well are you monetizing existing customers?

Since we have already taken a look at how to measure and analyze paid traffic and how many leads are converting to customers, let’s take a look at the evaluation of refund rates.

Refund Report

The goal of the refund report is to inform you of:

  • How much money you made.
  • What products people refunded.

To gather this information, you will want to look at whether your offer matches the way you’re selling it (successful or not) or whether something is not programmed well (maybe not able to download the item.)

Our good and extremely knowledgeable friends at Digital Marketer use InfusionSoft software to run their refund reports. (And it’s also great for emailing, membership management, payment processing and CRM, etc.)

Without a proper report of refunds it will be more difficult to see exactly what decisions you need to make to adjust your offers. Refund reports help you sculpt your offers to better suit the needs of your customers or maybe even help indicate if a product is no longer relevant to your market. Ensuring that your customers are happy with what they purchased is a good way to make sure your buyers become multi-buyers instead of “oops, I don’t want those items.”

This process is very similar to measuring the monetization funnel conversion rates. That is, measuring how well your pulling in revenue from existing customers.

Funnel Conversion Rates

Using Google Analytics, you can pull in data about how many came in at the front (or TOFU). You will follow what purchases were made along each step
of the way. Once you have that information, look at aggregate conversion rates to obtain the overall conversion rate for the period.
For example, often the number declines because the offer went to many who already bought the core offer. It is specific information like this that will help you decide if it’s time for a new core offer. Customers that have already bought in are your best customers, so you don’t want to lose them because of uninformed offer campaigns.

Diving Deep into Retention and Monetization Metrics

Let’s take a moment to gather our thoughts and refocus on the important goals of retention and monetization:

  • Turn buyers into multi-buyers: convince customers to make additional purchases.
  • Leverage the existing relationships — if they like you they will be more receptive to making more purchases.
  • Reduce customer churn: ensure customers stay engaged and on your list.
  • They’re keeping an eye on you.
  • They’re excited, aware of what you’re doing, and remember your name.
  • Maximize membership value: ensure that service and membership customers stay longer.
  • Keeping them a couple extra months represents a lot of opportunity

This is why the coveted concept of costumer lifetime value (CLV) is crucial to develop in your campaigns and analysis. The CLV is about how much your different audience segments are worth now and will be worth in the future. It is difficult to turn it into meaningful data in terms of defining and refining the group if you cast too wide a net. No one wants to spend too much time on a lot of data you cannot even use!

The goal of analytics like customer lifetime value is to figure out how much a specific subset of your audience is worth over a period of time. You can look at a specific group who took a particular action and you can look at purchases they made from the time they were converted or the time they made the purchase, up until the present day.

To do this, you should use a customer relationship management (CRM), like InfusionSoft. With this exported data make sure to include the following fields:

  • Total purchased
  • Total paid
  • Number of invoices
  • Average transaction value
  • If someone joined a particular lead magnet, for example, you can figure out what would you expect them to purchase.
  • Purchasers
  • Then look at how many opted in to determine how much the actual lead was worth

Let’s give you a comprehensive example with numbers to help drive the point across. We will use some metrics and data from Digital Marketer:

DM EXAMPLE FIGURES:
Transactions: 43
Total leads (opt-ins): 2,863
Total purchase value: 346.60
Total customers: 613
Leads to customers: 21%

Therefore:

  • Out of those leads, 21% became customers.
  • Take above rate and compare this to different lead magnets in the same period AND other periods to see how well you are converting leads throughout their lifetime average.
  • Then divide: [total purchases (212462)] / [total leads (2863)] = $74.
  • $74 is what every single lead is worth to DM over that time period.
  • Therefore, DM can say they acquire these customers for $X.
  • DM expectations: 10% to become immediate customers.
  • The nature of the funnel structure is that at each stage more and more people will not take the next step
As you can see, this gives you a good sense of which offers, lead magnets, and trip wires are converting to customers and which are going to generate the highest lifetime value. There are many ways to slice and dice your data. But using the process outlined above for your analytics strategy will help leverage your informed decisions for your business. [/et_pb_text][/et_pb_column][/et_pb_row][et_pb_row admin_label=”Row” make_fullwidth=”on” use_custom_width=”off” width_unit=”on” use_custom_gutter=”off” padding_mobile=”off” allow_player_pause=”off” parallax=”off” parallax_method=”off” make_equal=”off” parallax_1=”off” parallax_method_1=”off” column_padding_mobile=”on”][et_pb_column type=”4_4″][et_pb_post_nav admin_label=”Blog Navigation Section – Do Not Touch” saved_tabs=”all” global_module=”116279″ in_same_term=”off” hide_prev=”off” hide_next=”off” prev_text=”Previous Tip” next_text=”Next Tip” title_font=”Montserrat|on||on|” title_font_size=”20px” use_border_color=”off” border_color=”#000000″ border_style=”solid” /][/et_pb_column][/et_pb_row][/et_pb_section]

How To Ensure Your Money’s Well Spent: Pulling Paid Traffic Data

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Every dollar spent matters when you are trying to run a successful business.

Paid Traffic Data & Analytics
If you are paying for a service that in theory should help boost your revenues, you want to make sure you are spending that money well! Paid traffic is expensive, but if done well, can greatly help you reach your goals and your customer conversion rates!

Last time, we began to discuss the importance of making data-driven decisions. So we thought it to be beneficial to see how this method can be applied to paid traffic and the data you can collect.

What paid traffic does for your business?

  1. Generates interest:
    • Whatever you’re offering, you have an audience that wants it.
    • Paid traffic gives you a way to put your message, that you have a product, in front of that audience.
  1. Targeting options:
    • Segment and drill down to your specific audiences.
    • Says: “This is my primary audience; who wants to buy this?”
      Puts the message in front of them.
  1. Ability to scale:
    • Makes it easy to find new audiences to speak to.
    • Put the right message in front of them.
    • Help them become customers.

Continue reading “How To Ensure Your Money’s Well Spent: Pulling Paid Traffic Data”

Making Data Approachable and Useful: Data-driven Decisions

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As businesses and company proprietors navigate the success and growth of their respective businesses, decisions constantly bombard their every turn.

At every crossroad, businesses confront multiple options or directions from which they need to choose. Decisions based on intuition and/or market norms are very common, if not important to maintaining the mission or integrity of the company. analytic-and-data-course-image

According to an MIT study, companies that made decisions based on data collected were about 5% more productive and profitable than their competitors. However, using data is easier said than done. Success of data-driven decision management is highly reliant on the quality of data and how the data is utilized.

Why is data-driven management important?

A data driven business can make decisions on more than a hunch. More often than not, what you think will work for your customer isn’t going to work for them. Why? You’re not your own customer. A business needs to interact with the site and dig into the decisions they make and what makes them act. In addition to creating solid decisions based on facts, a business without data cannot grow. You’ll lack scalability, detailed insights, and will rely on your “best guess.”

Here at Up Automation, we want to help you make data-driven decisions to help you grow your business. Let’s get you and your business looking at the basics and get you on track to asking all the right questions.

Our Goal: to make data approachable and useful!

  • Provide tools and training to pick the metrics that matter.
  • Create accurate reports.
  • Make data driven business decisions to scale your business.
  • Use and trust your data.
  • Know where to look and have reports set up.

Continue reading “Making Data Approachable and Useful: Data-driven Decisions”

WAYS TO PROVE YOU’RE NOT A SPAMMER: How to Secure your Mailer Reputation

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Spam is the worst but for us who work in social and digital marketing, Spam is frustrating for a different reason

It’s reputation hurts ours! If you have been benchmarking or measuring the success of your email campaigns you will have been able to see how successful your open rate has been. It can be frustrating when you know your campaigns are continuously mistrusted and seen as spam.Mailer Reputation

FACT:
Worldwide, just 79% of commercial emails land in the inbox. This means for every 5 emails sent, 1 never reaches the intended recipient. [Return Path – 2015 Deliverability Benchmark Report]

3 WAYS TO PROVE YOU’RE NOT A SPAMMER

It’s your job to prove to the email service provider that you’re one of the good guys. But, you’re guilty until proven innocent. They assume you are a spammer before they assume you’re a reputable mailer.

It’s all about knowing what we are SUPPOSED to be doing.
When all is presented correctly, then they look at Engagement.
They don’t care if Engagement is good if we presented badly (as a “spammer”).

  1. MAILER REPUTATION
    • What are your volume and complaint rates?
    • What happened in the past?
    • What are you doing and not doing?
    1. SENDER INFRASTRUCTURE

Continue reading “WAYS TO PROVE YOU’RE NOT A SPAMMER: How to Secure your Mailer Reputation”