Meaningful data are extremely valuable for small businesses, says Streamlytics founder and CEO Angela Benton, but it’s your responsibility to find and use information ethically. We’re currently in a new era of data collection–and that’s for the better.
That’s according to Angela Benton, the founder and CEO of Streamlytics, a company that collects first-party consumer data transparently and aims to disrupt the current model of third-party mining of data from cookies and other methods that raise privacy and ethics concerns. Most recently, she was named one of Fast Company‘s Most Creative People for helping consumers learn what major companies know about them and paying them for the data they create while using streaming services like Netflix or Spotify.
In the latest Inc. Real Talk streaming event, Benton explainsthat she founded the company with minorities in mind, particularly the Black and Latinx communities, because of the disproportionate way they’ve been affected by data and privacy. For example, she points to the recent controversy over facial recognition data being sold to the police, which has a much higher error rate when comparing data of Black and Asian male faces, which could potentially lead to wrongful arrests.
“That becomes extremely important when you think of what artificial intelligence is used for in our day-to-day world,” she says, noting that AI is used for everyday interactions like loan applications, car applications, mortgages, and credit cards. Using her company’s methods, Benton says, clients can secure ethically sourced data, so that algorithms won’t negatively affect communities that have historically suffered from discriminatory practices.
Here are a few suggestions from Benton for finding data ethically without relying on third-party cookies.
Do your own combination of data sets.
“How [Streamlytics] gets data is very old school,” Benton says. Instead of relying on tech to combine data points, she says, you can manually compare data you already own and make assumptions using your best judgment. You may have data from a Shopify website, for example, about the demographic of your customers, and then you can go to a specific advertiser, like Hulu, for instance, to then target people that fit that profile.
Use your data to discover new products.
You can also look to your data to find common searches or overlapping interests to get ideas for new products, Benton says. Often, she says, she receives data requests from small business owners to discover ideas that aren’t currently on the market, for example, a vegan searching for a vitamin.
This combination method surprised Benton when she presented clients with data. “I thought it was going to be more focused on just like, “How can I make more money?” she says. “But we are hearing from folks that they want access to data to use it in more creative ways.”
Don’t take social media data at face value.
Benton and her company purposely do not source social media data because she thinks the data leave too much out of the full picture. You may get a customer’s age and “likes” from a social media page, but that doesn’t tell you what they’re searching for or what their habits are.
“That’s not, to me, meaningful data. That’s not where the real value lies,” she says. “We’re not focused on what people are doing on social media, we’re focused on all of the activities outside of that.” She gave a scenario where a consumer is watching Amazon Prime, while also scrolling on Uber Eats to find dinner.
Data signals are happening at the same time, but they’re not unified. It’s up to businesses to connect the dots. To Benton, that’s more meaningful than what you’re posting and what you’re liking on social media.
Covid-19 forced organizations to rethink the future of physical workspaces. Everything from desk layouts to conference rooms to communal areas needs to be approached with a new lens of employee health and safety. Data plays a critical role in how leaders structure their reopening plans, identify metrics for reopening and measure effectiveness.
Some countries are already reopening offices as the rest of the world watches and learns. One of the biggest lessons from the Asia Pacific region so far, as Gartner suggests, is the importance of “transparency” and “iteration.” As Hernan Asorey, chief data officer at Salesforce explained, “We are always assessing the data we have available to make decisions. For every evolving need, we pragmatically look at what exists from trusted sources, we vet it with experts in the field, and then we assess, augment, learn and adapt.”
Since organizations are faced with entirely new challenges—all dependent on a variety of factors including office location, workspace type and workforce size—leaders need data to inform a flexible approach to planning, informed by data.
There are four areas where data can inform your reopening strategy:
Creating a COVID-19 task force
Tracking regional policies
Informing workspace planning
Analyzing employee survey data
These areas represent a starting point and not an exhaustive list. Since all of these details vary based on your organization, this piece should be used for informational purposes only.
Reopening is a cross-functional effort. Organizations are instituting centralized, assigned Covid-19 task forces—made up of a variety of people with a diverse set of skills and perspectives—to manage details like workplace logistics and employee communications. This group should represent your workforce as a whole.
“At Tableau, we’re bringing together a variety of stakeholders into workplace conversations,” said Debbie Smith, senior manager of workplace at Tableau. “We have perspectives—and data—from all aspects of the company, from security to HR to real estate to marketing to procurement. We’re also bringing in outside experts to inform details like capacity planning and air filtration.”
All of these stakeholders work with different data points to inform their perspectives. For example, health and safety teams might monitor regional policy data, procurement might use data to inform any new equipment purchases, like panels between desks, and IT might work with workplace teams to determine how to replace existing equipment like phones or headsets.
Creating a dedicated team is a foundational step in a reopening strategy, because data is useful only when people can provide context and take action.
Reopening strategies are largely dependent on local policies. In addition to these policies, organizations are also faced with a long list of guidance from the Occupational Safety and Health Administration (OSHA), the Centers for Disease Control and Prevention (CDC), the Environmental Protection Agency (EPA) and more.
Organizations are exploring centralized dashboards to track changing policies and to inform key indicators to determine when it is safe to reopen offices. SC&H Group’s data analytics team, for example, created a sample dashboard that shows what this could look like for a company in the United States. The dashboard highlights legislation on a state-by-state basis alongside a map showing number of cases.
Sample dashboard from managing consulting group, SC&H Group that displays local policy data alongside regional case data. Interact with the full visualization.
Christopher Adolph, associate professor of political science and adjunct associate professor of statistics at the University of Washington, is curating and maintaining a data set on state policies related to Covid-19 from open source data. He encourages data and analytics leaders to take a focused approach when visualizing local policy data. That might mean considering other visualization types beyond maps to focus on specific, regional metrics that show the impact of Covid-19.
“If I were an organization,” shares Adolph, “I would structure a visualization to show what’s happening in each location associated with my business, with filters that allow stakeholders to sort through stringency of policies, trends in mobility and trends in cases. I would want to see a time series of how policies change over time as cases increase or decrease in a region.”
Data analytics and geospatial services firm Lovelytics created a dashboard template combining Covid-19 case data from the Tableau Covid-19 Data Hub with sample HR data, providing a breakdown of at-risk employees by building, age group and location. Although this example was originally developed for companies looking to stabilize in a crisis, these types of dashboards could also become a single source of truth in the event of another wave of the virus after reopening.
Tableau partner, Lovelytics, created a COVID-19 and human resources dashboard solution to analyze risk by location. Interact with the full visualization.
Some of the most complex challenges that employers face in the wake of Covvid-19 are related to workspace layouts. Many organizations have adopted open office concepts, making it difficult to enforce six-feet guidance between employees. They’re also evaluating the use of shared spaces like kitchens, bathrooms and elevators along with high-end air filtration systems to reduce the spread of infectious droplets. One way that employers can start to make sense of all of these logistical decisions is through data.
Some key data points that employers are collecting (or considering collecting) around space utilization are:
Physical distance (between desks and in shared spaces)
De-densification (removing furniture in communal spaces like kitchens and conference rooms)
Air movement and ventilation
Pinch points like elevators and bathrooms
These new challenges are leading organizations to take a new approach to workplace metrics. Salesforce, for example, is analyzing data to model staggered arrival times so they can effectively manage elevator capacity. Salesforce is also partnering with Siemens on key solutions for a “touchless office,” where organizations can manage occupancy and location data to augment their contact tracing process (on an opt-in basis).
Global commercial real estate services firm Cushman & Wakefield noted in its Recovery Readiness guide that organizations may want to “invest in operational building technologies that enhance the integration, visibility, and control of building and workplace systems” (like occupancy sensors or air quality monitoring capabilities). The company also piloted a new office layout in Amsterdam deemed “The 6-Feet Office,” using large circles and visual cues to enforce a six-foot separation between employees.
An example dashboard from Tableau Zen Master Ken Flerlage. Note that this is intended to be an example and not a template. There are a variety of factors in workplace planning that organizations need to consider beyond the six-feet guideline. Interact with the full visualization.
Recently, Tableau Zen Master Ken Flerlage explored what an office space visualization could look like, drawing six-feet circles around each desk. If a desk area doesn’t follow the six-foot perimeter, then the circle turns red and indicates that the company needs to rethink the layout of that office area. In Flerlage’s blog post about the visualization, Amanda Makulec, data visualization lead at Excella and Bridget Cogley, senior consultant at Teknion, explain that this template is a good starting point for people as they rethink office seating arrangements, but that there needs to be additional thinking around the complexities of how people move in an office setting.
To account for these complexities, some companies are hiring external experts to help set these parameters and inform logistics planning. All of these concepts will require additional iteration and flexibility as organizations put them into practice.
Whether or not they can physically return to work, organizations also need to think about employee needs. Are employees comfortable returning to work—and if so, in what capacity? Some employees need to stay home with kids as schools remain closed, others may have compromised immune systems, and some may just be more comfortable working from home until a vaccine is available to the public.
Some companies, including Tableau, are gauging employees’ concerns through regular surveys. They’ll ask questions about general well-being, like how they’re adapting to work-from-home and how the company can support them. Companies in the logistical planning stages might ask questions about whether or not employees are comfortable returning to work to determine reopening schedules.
An example dashboard from the Tableau people analytics team showing results of a COVID-19 work-from-home survey (this dashboard contains sample data). Interact with the full visualization.
With this data at their fingertips, organizations can analyze:
Employee needs like office equipment or childcare support services
Once offices reopen, companies could join this survey data with utilization data to understand how many employees are actually coming into the office on a regular basis. This can help inform whether or not employees are comfortable with new working conditions.
Analyzing the results of these surveys can help organizations develop important metrics around how the pandemic is affecting their employee base and help them determine how to take action.
From connection through collaboration, Tableau is the most powerful, secure, and flexible end-to-end analytics platform for your data. Elevate people with the power of data. Designed for the individual, but scaled for the enterprise, Tableau is the only business intelligence platform that turns your data into insights that drive action.
Big data as a concept is thrown around a lot. It’s often used as a buzzword to sound tech-savvy and on the ball — but how much do you really know about it? In truth, it’s been around for decades. Businesses have been analyzing their customers’ actions and behaviors and using it to inform their business decisions for a long time; it’s the marker of a strong businessperson. The difference today is that we now have the tools and technology to gather and analyze larger amounts of data faster. Enter big data.
You don’t have to be a tech genius or a data scientist to make big data work for you and your business. Here are seven areas where you can use big data to streamline and optimize what you already have, with key examples and actionable tips to get you started.
1. Website design
To prove that big data is not only for the scientists of the world, let’s start with a more creative example. A well-designed website shouldn’t only look good, it should be part of a subtle conversation going on between you and your customers and leads.
One way to gather useful big data from your website is through heat maps. You can see exactly where the eyes and cursors of visitors to your site spent the most time. If these heat spots aren’t on your CTA button, contact form, or wherever else you most want them to go, you know what needs to be changed. You can achieve similar results with traffic analysis — looking at page views, unique visitors, visit duration and more. Many traffic analysis tools will also let you compare to your competitors’ sites to get a bigger picture of the general landscape.
2. Campaign timing
Have you ever put together a five-star marketing campaign that ticks all of your customer persona boxes, looks great and has a punchy CTA — only to see it flop? The greatest campaigns in the world will get you nowhere if you don’t publish them at the right time.
Whether you’re publishing on social media, email or any other digital platform, there are tools (like Growbots for email or Sprout Social for social media) that will gather data for you about when your audience is most active, when they are most prone to engaging and ultimately when the best time to reach them is. With big data, you don’t have to take a stab in the dark about when to launch a winning campaign.
3. Conversion optimization
There are a lot of variables when it comes to on-site content. While that may seem daunting to some, that really just means that there’s a lot of room for optimization so that your business can do even better than it is now. From headline copy to page color scheme, it can all be tweaked and improved to gather the highest amount of conversions possible.
Big data analytics can help us to understand how leads travel through our sales funnels, where they might get lost and at what point many prospective customers drop off. Data-driven optimization is the fastest and most efficient way to get it right. Even while experimenting, be sure to gather as much data as possible and analyze it in bulk for the most accurate and informative results.
No matter what your business is, at the end of the day it will come down to people making a decision. Big data might seem like a huge and faceless tool, but it can also be used to add more personality and individuality to your marketing and customer interaction.
The fashion brand, H&M, used big data to do exactly that when they integrated it with their chatbot. As it offered options to prospective customers and asked them if they liked the product choice, it learned more and more about what clothing options they liked. Along the same vein, for marketers to make personalized decisions that will have a real impact on leads and customers, we need to learn about them first. Big data is one effective way to do so.
5. Customer retention
A good business person knows how to attract and win clients. A great business person knows how to keep loyal customers. Once again, big data can take the heavy lifting out of this process.
Checking in with your existing customers through quick surveys and polls is one way to be continually staying in touch with how they perceive your company and what they think of your products or services. It’s anywhere between five to 25 times more expensive to find a new customer than to retain an existing one, depending on your industry. Use big data to regularly make sure that you are doing exactly what your existing customers are expecting of you.
6. Informing risk management
Risk is a fact of life for any business. Wouldn’t it be great if we could find a way to make smarter strategic decisions with key data to back up our more risky ventures? With big data, that could be a reality.
UOB Bank in Singapore did it. As a financial institution, making a misstep in risk assessment and management could be catastrophic. The bank used big data to develop a risk management system that cut down their risk analysis time from 18 hours to just a few minutes. Being able to carry out extensive risk analysis in real-time was a game-changer.
Of course, not every business has the ability or the resources to create their own risk management solution from scratch but there are tools out there that help businesses accurately quantify the risks they take on a daily basis, shedding light on one of the trickiest parts of business decision-making.
Think about the most successful businesses in the world — Amazon, Apple and Microsoft, just to name a few. They didn’t get to where they are today by sticking to their first idea and running with it. They diversified, innovated and kept up with other demands from their customers. Often, it was big data that showed them the way.
Let’s look at Amazon’s recent venture, Amazon Fresh. To launch their whole foods service, Amazon focused on big data analytics to not just understand how customers buy groceries, but also how suppliers interact with grocers. Big data helped them understand the whole supply chain and find a solution that streamlined every aspect of it, thereby providing an innovative and helpful service.
By: Sina Fak / Entrepreneur Leadership Network Writer
How well do you understand your customers? Whether your brand is B2B or B2C, your customers expect seamless, omnichannel experiences. Especially during the Covid-19 crisis, customers expect brands to offer value, relevant products and services, and to grow with them as their needs evolve.
The pandemic has taught businesses that staying relevant in a time of crisis requires a deep, holistic understanding of the customer, and an openness to new ways of doing business. To stay ahead of such rapid change, customer intelligence and data is more important than ever. From remapping and re-creating customer journeys, to developing more accurate forecasting models, all businesses need a data and analytics strategy that allows everyone in the organization to see customers needs in real time and build scenarios, identify gaps, stress-test ideas and improve results with actionable insights.
Your customer is expecting you to lead, and it’s never been more important for your brand to address their pain points and deliver exceptional experiences.
While the long-term economic and societal impacts of the pandemic are yet to be fully understood, customer attitudes and behaviors have already shifted in profound ways, and some of these changes are predicted to continue into the future. Recent consumer surveys reveal how rapidly behaviors are evolving:
68% of people report that the pandemic has changed the products and services they think are important
75% of people using digital channels for the first time will continue to do so
In Italy, e-commerce sales for consumer products rose 81% in a single week and in the UK, 20% of people say they won’t buy fashion in-store again
In the retail sector, the shift to online buying and direct-to-consumer selling, coupled with a decrease in discretionary spending and flat sales for net-new products, has forced businesses to change their business models overnight. Traditional B2B businesses like financial services organizations are not far behind, augmenting existing sales and service models so they can better serve customers remotely. In the healthcare sector, patients can now choose telehealth as a standard alternative to an in-person visit—and adoption has been swift: one of Europe’s largest telehealth providers, KRY International, has seen a 200 percent increase in registrations. Government agencies and educational institutions are also finding ways to deliver their services in a virtual world.
But meeting the customer “where they are” is not just smart business—it’s essential for survival. Business segments that aren’t responding to changing customer preferences by accelerating their own digital transformations will be left behind. And a central part of transformation includes prioritizing customer analytics.
In today’s competitive and uncertain market environment, your advantage lies in understanding what resonates with your customers. How businesses choose to respond will influence buying decisions today and in the future.
What kinds of customer experience metrics are valuable in order to gain understanding of your customer? To create baseline analyses, you need behavioral, transactional, and feedback metrics. And as Gartner points out, more frequent, real-time monitoring of customer metrics is essential during this crisis, since attitudes are changing so rapidly. Useful metrics include:
Customer satisfaction scores
Customer effort scores
Net promoter scores
Customer call volume and types of queries
Website behavior
Point-of-sale data
Geospatial data
Social media sentiment
Employee feedback
Every business, regardless of industry segment, should also expect to field new questions from customers about products, logistics, inventory, supply chain, and operations—and every business needs to be prepared to capture this feedback and respond.
01. Strategic Dashboard
Potential Users: C-Suite, VP, DirectorObjectives: At-a-glance cohesive data storyInsight Examples:Performance and comparison metrics tracked against enterprise goalsExample: Executive Summary dashboard
Potential Users: CRM Support Teams, Website Managers, Marketing ManagersObjectives: High-level, real-time monitoring and managementInsight Examples:Retail and customer satisfaction KPIs, marketing campaign performance, inventory statusExample: Store-level Product Availability dashboard
Things definitely look different now, and they are different. When every aspect of your operation is under scrutiny, you need information, quickly, to make the right decisions for your business and your customers. Understanding customers and their expectations has always been a priority for businesses looking to create competitive advantage, but the pandemic has proven that businesses must have an even stronger line of sight into what their customers need.
You need to be prepared to proactively respond to rapidly-evolving behaviors and perceptions. As David Leonhardt notes in a recent New York Times op-ed, “When the economy weakens, people have to make decisions about where to pull back.” By using data insights to understand and adapt to new realities, you can give your customers reasons to remain loyal and eliminate some of the uncertainty facing your business.
What untapped insights are waiting to be discovered in your customer data?
From connection through collaboration, Tableau is the most powerful, secure, and flexible end-to-end analytics platform for your data. Elevate people with the power of data. Designed for the individual, but scaled for the enterprise, Tableau is the only business intelligence platform that turns your data into insights that drive action.
