5 Takeaways from Tableau

In October, SIGMA Data Scientist, Adam Smith attended Tableau’s coveted conference in New Orleans. Today he shares his biggest takeaways:

1. Mobile is now

One theme across many conference sessions included the importance of creating dashboards that work across screen sizes: desktop, tablet, and mobile. Fortunately, Tableau has a Dashboard Layout tool that allows you to create multiple versions of the same dashboard to optimize the display on different device sizes. Coming in 2019, there will be a default mobile view so that even if a dashboard never had a mobile version created, it will automatically transform into a mobile friendly view. This not only helps with older views but can make it faster to create custom mobile dashboards for your new projects.

2. Natural Language Processing (NLP) is next

Tableau’s mission is to help people see and understand data, but when they say people, they don’t just mean data scientists and spreadsheet wizards, they mean everyone. Even if you’re the type of person who thinks pie chart sounds like a tasty snack, they want to help you. An upcoming version of Tableau will have NLP built right in. This means you can write questions in English like “What are our sales in Q3 2018?” and Tableau will return the data in the best visualization. From there you can add additional text like “in the northeast region” to filter and drill-down or adjust it with the standard Tableau tools.

3. Interactive is best

I was reminded again that we need to make sure our SIGMA dashboards are interactive, flexible, and easy to use. It’s simple to put together a few charts, add a few filters and think you have a great dashboard, but it’s important to put yourself in the end user’s shoes and see what happens when you click on a bar chart (filter actions) and think “how can I make this dashboard work for a lot of people at once (parameters)?”

Here is a dashboard SIGMA created for SIGMA. It outlines work hours for each week and identifies when it gets off balance.

Of course you want to get feedback from your end user, but they may not know how to articulate their experience when it comes to options for interactivity.  Consider giving your dashboard to a colleague who is familiar with Tableau without telling them much about it to get feedback not only about interactivity, but anything else they may notice.  Looking at a dashboard with fresh eyes can help you really make it shine.

4. Who is this dashboard for?

Amid all the deeply technical sessions that I attend, I always try to make room for at least one session on soft skills.  Last year that was Design with the user in mind.  This year I checked out Start at the beginning | Gathering requirements for dream dashboards.  The presenter had lots of great ideas for making sure you’re building what your end user really wants.  Here are my top takeaways:

  1. Find the end user – Make sure you find who will really use your dashboard. Ask them open-ended questions about what they are trying to accomplish.
  2. Do it in their style – Use colors and chart types that work well for them.
  3. 3 x 1 rule – For every three things we do for our audience, we can do one thing for ourselves.
  4. Easter eggs – Put in something that will surprise and wow the user.

5. Fun!

There are hundreds of breakout sessions at Tableau, not to mention the hands-on training, Tableau Doctor, and insightful conversations in the hallways with fellow attendees. But it’s not all work and no play for attendees.  There’s plenty of fun to be had at receptions, mixers, and happy hours, and that’s even before you check out the jazz clubs on Bourbon Street! That is all just prologue to the last night of the conference and the party with 17,000 data nerds: Data Night Out.  This year it was at the Superdome.  We ran out onto the field where the Saints play each Sunday and had a huge, nerdy party.

The Tableau Conference is a great way to stay on top of what’s new and next at Tableau.  If you weren’t able to attend, but would like to learn more, many sessions were recorded and are available for free on the Tableau Conference website. And if you’re really excited, it’s not too early to sign up for 2019 when Tableau Conference returns to Las Vegas.

Successful Analytics

At SIGMA, we believe that certain processes effectively guide and instruct the B2B marketer to optimal performance and maximum ROI. Furthermore, an understanding of B2B marketplace realities is essential to appropriately apply these principles. The proper understanding of data can reveal these realities while the proper use of data can inform application of the principles.

Price’s Law (or the Pareto Principle), is a phenomenon that economists, and even scientists, have recognized as a fundamental aspect of both human interaction and the natural world. Simply stated, it’s the uneven distribution of resources or productivity to relatively few within a particular domain. The size of cities, the height of trees in the Amazon Rain Forest, the size of galaxies, and even sales and profits reflect the Pareto Principle. In business, we observe the principle in the fact that about 80% of your sales comes from about 20% of your customers.

What does this fundamental landscape of the business world mean? It means that how and to whom you apply your marketing efforts affects the bottom line.

With this law in mind, there are two approaches that work best for all marketing efforts.

Align the most important aspect of your marketing efforts.

  • Prior to implementing any marketing efforts, if you and your team define one metric, for example lead generation, as most salient, you will drive the effort in a more focused manner. A focused marketing effort is much more likely to land a client who will be in the 20% that generates 80% of your sales.

Create a roadmap to incorporate each marketing activity into a larger body of efforts.

  • Just as sub routines make up your morning routine, each sub marketing effort should have a directed purpose that is part of the overarching marketing effort. While seemingly obvious, if your business moves from one effort to the next without a thematic thread, then maximum efficacy of your effort is lost and ROI will be average to poor.

Once solid methods are in place, an easy extrapolation from your data will give insight into your winning tactics. Insights into your winning tactics can easily create the optimal approach for all platforms, digital, email, social or otherwise that maximize ROI.

For a deeper analysis of this topic, we invite you to explore the attached eBook B2B Data 101, and subscribe to our blog for other compelling content related to data and how it can work for you

Adam Smith Speaks at the ABA Bank Marketing Conference

Check out Adam Smith delivering a great presentation on “Data and Machine Learning Worth your Time and Money”. Adam gave this speech at the American Banking Association’s 2018 Bank Marketing Conference in Baltimore, Maryland on September 24th. In this video he explores such customer segmentation, customer profiling and predictive modeling. He, also, wrote this blog on the same topic.

 

 

Please like and share the YouTube video and/or subscribe to our channel for great future videos and clips like this.

9 Key Marketing Metrics Every Company Should Measure

When organizations begin to standardize marketing measurements across their sales channels, business units and media, they will better track Brand Equity, Market Share, Marketing ROI, and Product and Customer Profitability.

Here are 9 metrics every marketing organization can be measuring:

  1. Multichannel marketers are tracking the costs to generate traffic to their sites from all possible sources. These often include the costs to complete the transaction, which can include a call center or technical support of the site itself.
  2. Marketing Spending Metrics are often looked at to try to establish the ROI value of incremental spending. Some of the measurements in this area include cost per impression, reach, frequency, share of voice.
  3. Visitor Acquisition KPIs are used to understand the health of the sales funnel. Definitions begin to get very important here – what is a visit, what is the source of the visitor, what is a return visitor, what is a unique visitor, etc. Tracking sources often require the integration of multiple reporting tools – the ad serving provider, the web tracking tools, the ad tracking tools, etc.
  4. Site Effectiveness Measurements look at the conversion effectiveness of the site. The sales funnel is critical here – how efficiently can a visitor be turned into a customer?
  5. Definitions are critical in conversion metrics – especially if the conversions of one channel are to be compared to others. What does a conversion mean? The problem of properly attributing conversions to their sources is common and must be consistent across each channel.
  6. Buyer Metrics includes the frequency of purchases, or the retention rates of customers that can be rolled up to overall market share, brand equity and/or customer lifetime value. The most quoted Buyer Metric is typically the Average Order Value, or the AOV, which is used to understand and compare different groups of buyers.
  7. Revenue — Multichannel and e-commerce marketers track revenue carefully to compare the margin generated from each channel, to determine the value of incremental sales, and to guide pricing and promotion decisions.
  8. Customer Loyalty and Customer Profitability Metrics — Companies use these metrics to understand the value of their individual customers, regardless of which sales outlet they have chosen. Definitions are critical from one channel to the next, and the methodology for the measurement of loyalty and customer-level profitability can vary considerably from company to company, depending upon the purchase dynamics of the product.
  9. Profitability and ROI — Each of these categories of metrics can include components such as:
    • Channel margin
    • Performance compared to a sales target
    • Net Profit
    • Return on Sales
    • Return on Investment
    • Net Present Value (NPV)
    • Return on Marketing Investment (ROMI)

Any one of these metrics are difficult to measure without integrated databases to create definitions across channels. As data tools advance and simplify the process, marketers increasingly have the ability to measure such metrics easily. Today, smart decisions across the marketing organization can and should be commonplace.

3 Ways to Get to Know Your Customers

Today, online purchases and order forms are rapidly replacing the face-to-face or voice-to-voice interactions that drove business and relationships in the past. However, computer-based interactions have also opened up new methods of understanding your customers, and have highlighted the need for a solid customer database. Key data provides crucial information to B2B companies about key traits, including purchasing style, to help you further engage, market to, and acquire more customers. Here are 3 data sources to help you better understand your customer:

1. Understand Customer Transactions

Ask yourself: what types of trends do you see when you look at your transactional data? Are your sales up or down from last year? What are the common products/services that are being purchased?

Simple questions like these can typically be answered using transactional data. Before you dive in too deep, try to understand the big picture of what is being sold and purchased as a whole.

Reflecting on the past helps better us in the present and look ahead to the future.

Your company may be tracking customers through Facebook with digital efforts such as retargeting.

2. Know Your Customers

It’s great to know what products or services your customers are purchasing, but being able to identify individual customers may be the single most useful tool available to the analytic marketer. For some companies, this is easy; their transactional data has the customer information by nature. For others, they rely on loyalty programs or survey data to make generalizations about the purchases their customers are making. In both cases, identifying new and returning customers will help your company understand current trends in their business.

Unsure how your company is tracking customer activity? Ask your sales team what information is being kept in a CRM; you may find that the information is already available.

3. Who’s Who – Tracking New vs. Returning?

Once the identity of the customer is known, you can begin to understand who is a new vs. returning as well as begin learning about the types of customers who might be interested in purchasing from your company. This is important data that can be found by bringing in outside data sources with demographic or firmographic information. Once you can identify key customer traits, you can create customer profiles for those who are likely to become new, those who are likely to leave, or those who are the most profitable.

5 Ways Data Can Help Guide Your Digital Marketing

As digital marketers, we are always striving for higher open and click-through rates and increased page views, but often rely on instinct and guess-and-check methods to reach our goals, instead of making decisions based on results. That’s where data comes in.

Using data to guide your digital marketing strategy can take it from its likely generic approach to one that tailors messaging and places relevant content, based on actual findings, on the right platforms for your intended audience.

For help transitioning your digital marketing approach to one with data-driven strategy, follow our 5 tips below:

  1. Use Custom Audience Targeting – If you have first-party data from current customers, use it to develop customer profiles based on demographic and psycho-graphic factors. These profiles can help you develop tailored content based on factors such as age, gender, geography, and interests. Creating a targeting strategy with first-party data can help you market to current and potential lookalike customers with messaging they will likely interact with. If you don’t have enough first-party data, try using the targeting tools offered by digital platforms.
  2. Determine Your Distribution – Not all digital platforms will work with your digital strategy, because your target audience is not using all of them. Use your customer data to determine what social and digital platforms your audience is most likely to be using and start there. If you don’t have enough information about your current customers to make this determination, look at what platforms your closest competitors are using and see which fit your brand the best.
  1. Let Data Drive Your Content – Measuring the success of your content can be your greatest tool in determining what new content to develop. How will you know what content to create in the future if you don’t know what is resonating with your target audience now? Using data from your digital marketing campaigns can help you determine what content is working with your audience and help you determine what to focus on for future content. In addition, use this information to edit or reformat existing content that may not have performed the way you had hoped. Editing and reusing existing content based on your findings can save you time and development costs.
  2. Time Your Content – If you have been using data to track interactions with your content then you should have an idea of the time of the year, day of the week, and even the time of day your target audience is most likely to be online. Use this data to schedule your content during those peak times for a better chance of meeting your campaign goals.
  1. Make Reporting Easy – A major challenge for data-driven digital marketing is the time is takes to retrieve the data from all of the different distribution platforms that you are using for your campaigns. Website, email and pay-per-click marketing rarely use the same tool, which can complicate your reporting. In order to optimize your digital marketing data, consider combining it all into one dashboard that allows you to see trends that may be happening across multiple platforms.

To learn more about data-driven digital marketing or to schedule a demo to see our reporting dashboards, contact us at info@sigmamarketing.com or comment below.

Jump Start Your Bank’s Data-Driven Marketing Program

Data has been the buzzword de jour over the last five years. Still, most banks haven’t moved beyond data being “nice to have.”

On September 24th, SIGMA Data Scientist, Adam Smith, will be speaking at the ABA Bank Marketing Conference in Baltimore and giving a presentation about Data and Machine Learning Worth Your Time and Money. Data is big and messy, but this session will help you understand a few key areas of focus and how you can become a more data-driven marketing leader within your organization. In his presentation, Adam will discuss five strategies to jump start your data-driven marketing program, as they are outlined below:

  1. Profiling and Base-lining – Append demographic data of existing customers to better understand those you are doing well with and those you are not.  Also look at key metrics to identify baselines and trends.
  2. Customer Segmentation – Did you know you can use generic segments from Experian, Nielsen, etc. or create your own? Either way the segments can help better target marketing.
  3. Smarter, Deeper Analysis – By applying the results of steps one and two, banks can more easily identify better cross-sell targets.
  4. Dashboards and Reporting – Once you start to become more data-driven you’ll notice the request for reports will increase.  Creating dashboards that are connected to live data has several benefits including creating a single source of truth and allowing end users to identify more insights than static reports.
  5. Modeling and Prediction – Once you understand your customers, have made some wins with targeted cross-sell, and have your dashboards set up, it’s time to move on to predictive modeling.  Predictive models combine many variables related to demographics and behavior into one simple score that can be used to guide your marketing efforts.  They use advanced statistical techniques to identify those who are most likely to become a customer, buy a particular product, or close an account.  Once you have this information in hand, you can act on it to improve acquisition and retention, while deepening customer relationships.

Come join us in Baltimore to learn how to get started, hear specific success stories, and have the opportunity to ask questions applicable to your organization.  After the session is over come up and say hello—We look forward to meeting you!

B2B Data 101: Our Approach to Data

Often we are asked: what makes SIGMA’s data solutions different than others’ services and platforms? Simply put, we provide the best way to display and visualize unique metrics that inform important decisions at your company. Our approach to data sets the stage for everything we do!

The way people currently talk about data can make it seem like a difficult topic to grasp. From clean data and dirty data, to smart data, big data and partner data, as well as geographic, demographic, or firmographic data. What do all these data phrases have in common? They’re not too difficult to understand, if you have the right data partner.

Our Data Process

Your company continues to collect data from your clients and prospects, yet this data is most likely “dirty” — incomplete or overloaded with duplicates and inconsistencies. At SIGMA, we use multiple methods to  “clean” your data, including ensuring each record is complete and not re-entered somewhere else. Once your data has been through the cleaning process, we enrich it further by adding third-party data sources like geographic data or partner data and statistical model scores for prioritizations that boost your data to “smart” status.

Before sharing the data with you, our top data scientists run a variety of analyses to present insights that inform and transform. These insights are more actionable than relying on a CRM or other marketing automation tools alone, and effectively point your sales team to the right clients, showing your company how to grow or alert you to clients that may be leaving. With decades of experience, our data scientists pore over your data looking for insights, opportunities, and solutions to your most-pressing problems. We demonstrate these insights via dashboards, which are fully accessible through your mobile device.

A Continuing Data Strategy

Most companies stop there, but at SIGMA we realize the untapped potential of unmeasured client and prospect data. We strategize with you to understand ways to mine future data insights from new data sources because the more clean and enriched data you collect, the more in-depth our insights become.

SIGMA’s data approach is varied and flexible, always ensuring quality data gets back to you in the form of useful insights to drive your business decisions. We will always work with you to maximize your data resources and transform your business.

For a deeper analysis of this topic, we encourage you to check out the eBook “B2B Data 101” here, or subscribe to our blog for more interesting posts related to data.

“Smart” Data Can Help You Align Marketing and Sales

Sales and marketing team alignment is more important than ever! Our partner Hubspot reports that companies that get marketing and sales working together not only generate 208% more revenue from their marketing efforts – but they see 36% higher customer retention and 38% higher sales win rates.

Where does data fit into this alignment? Capitalizing on customer intelligence and making insights and clean data available to Sales can lead to a more efficient and effective process that can motivate and fire up your sales teams. Get started by using these analytical techniques:

Create Common Sales Cycle Definitions Across Marketing and Sales

Your sales team lives and dies on what they call leads, but Marketing might have a very different definition. Adopt a common language for each stage and definition of the sales cycle. Whether you use Prospects, Inquiries, Marketing Qualified Leads (MQLs), Sales Accepted Leads (SALs) and Sales Qualified Leads (SQL) or some other set of opportunity ratings, collaborate to define each stage across Sales and Marketing –so you can all start working towards the same goals, and be able to understand each other’s measurements.

Data Dirty? Build the Case to Invest in Clean Data
Both sales and marketing hate dirty data – but how much revenue is it costing your company? Build some scenarios for better demand generation and increased close rates with better data – you’d be surprised how much lost revenue can be picked up with just a lift of 5%!

Here are some ideas for the metrics you might use:

 

Add a Score to Your Leads

Nothing will kill Marketing’s demand generation credibility faster than a bunch of unqualified leads being sent to the Sales team. Sales probably shouldn’t make a call until you know there is a budget and a timeline. Maybe lower cost sales channels like email or outbound telemarketing can be used to collect the missing data before a lead reaches an acceptable score. Alignment on the meaning of a “good lead” can really reduce friction and time to close.

Build a Common Definition of Your Segments – and Assign all Prospects and Customers

Building personas for web development won’t help the sales team much if they never see those types in the market place. Find real customer segments that purchase in distinct ways, and help the sales teams craft a USP for each segment that will give them a better shot at creating opportunities. Then, make sure each prospect and customer is assigned to a segment so sales can put that messaging to work on the ground.

Find Your Territory Gaps

Use your customer and prospect data to find the holes in territory maps where you have low coverage but high potential. You can often pull much more opportunity out of an area with better or more salespeople. Marketing often has the data to help make these decisions, but Sales is the team that needs to make decisions about coverage.

Use Purchase Likelihood Scores for Call Center Targeting

Outbound phone calls are not inexpensive and turnover in telesales can be high. Invest in reaching only the highest priority prospects by using predictive model scores in your call center. Focusing calling from the top down – best to worst prospects. This should cut the calls needed, improve team morale, and increase the success rate significantly.

Your marketing team should be able to add these types of smart data to customer and prospect records – and both Marketing and Sales can get aligned around your target and your critical asset – your data.

Creating Smart Data

If you and your team are spending time trying to wrangle all your various data feeds to find a way to create opportunities for your organization — there is a way to streamline your efforts.  You don’t need to find a home for, and a way to use all your data — just the “smart data”.

The flow of data is picking up speed for all marketers, and astute leaders are turning this data into better, more targeted and relevant sales and marketing efforts. But managing all the data from web platforms, marketing technology, mobile devices and the “Internet of Things” is often a daunting and time-consuming task. Rather than focusing on managing the big data flow, we think marketers should try to discover the relatively few data points that can really drive revenue – find your smart data and put it to work!

Start with Customer Segments

The simplest way to begin data-driven messaging to customers and prospects is by understanding that different segments may purchase your products for different reasons or in different ways. For the B2C client we find that demographics or lifestyle factors drive differences in product usage, and for the B2B client – different industry verticals, or other firmographic data mean different likelihoods to buy products and services.  Are you able to accurately identify these customer segments and analyze the differences in how they purchase or use your products and services?

Find Your Customers’ Trigger Point

Often times your customers will take some specific actions before they buy – or before they say good-bye (for example, checking their balance before paying off their car loan).  These actions should be seen as prompts that can be used to trigger communications to make the sale happen faster, or keep a customer longer. Using predictive models can score your customers and prospects for their likely purchase propensity – but the model itself can identify the behavior triggers that can be turned into automated messaging programs.

Build an Engagement Score

Measure how engaged your customers are with your brand by creating a score that will combine interactions across channels (email, satisfaction, service calls or visits to the store). Keeping it simple with a High-Medium-Low engagement scoring process, you can easily tell if some customers just need more love!

Add “Data Transformations” to Your Data Clean Up

When you combine data from multiple sources you might receive basically the same fields from the different data sources – although they may have different names and slightly different values. For example, “current age” is not as easy to update as “year of birth,” and may actually be the most useful data element for use in marketing campaigns. Build common rules, definitions and data naming conventions so the data can be easily understood, and used efficiently in marketing, sales and operations.  Data Transformations are key to making your data smart and actionable.

Trying to gain control of all the data generated by your marketing today can actually slow your progress to a more innovative data-driven approach.  Quality over quantity is key! Find your top ten “Smart Data” elements, use them to test more relevant multi-channel efforts, and build in more variables as you grow.