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Data is the most powerful asset marketers have available to them. At the same time, using that data effectively is one of the most challenging aspects of the job. In this month’s webinar, we’ll share the marketer’s blueprint for data strategy.
Digital marketers, brace yourself, the holiday season is on its way! Although autumn is just a few weeks old, now is a pivotal time to outline your digital approach for the holidays. Nowadays, most consumers have shifted from the in-store holiday shopping madness to shopping from the comfort of their home or in front of their personal devices. In 2018, consumers spent over $120 billion during online holiday shopping (across 61 days 11/1/18 - 1/1/19), which was up 16.5% from 2017.
This blog post is designed as a guide to help digital marketers prepare their programs effectively and help capitalize on the increased seasonal consumer demand while maintaining performance goals. We’ll run through key tasks that all digital marketers should be checking-off prior to the holiday up-tick to ensure a well-rounded strategy and the best chance for success.
One good method of benchmarking and level-setting expectations is by reviewing last year’s performance to gauge how you should approach the program strategically this year. When reviewing last year's performance, make sure you’re comparing days of the week and isolating pivotal days like Cyber Monday, Black Friday, and Christmas Day. We know that these days act differently to other days throughout the year, so you should treat them like the special cases they are. Other questions you should be asking yourself to help make strategic decisions are:
It’s essential to understand and leverage last year’s performance and data to help make informed decisions on this year’s approach. As the saying goes, “If it ain’t broke, don’t try to fix it”; this can be applied to your digital marketing holiday strategy as well. Look for key areas that showed strong performance against your KPI last year and approach them in the same manner as the last holiday season.
Just like Good Ole’ St. Nick, you need to make sure you’re building your audience lists to help set yourself up for success. If you already have an expansive list of audiences you’re remarketing - great! You’re a step ahead of most marketers. One thing you may want to consider is recycling last year’s holiday audience lists to see if you can garner the less frequent purchasers. However, be aware of any site or program changes over the last year that could’ve impacted those lists.
For readers that don’t have any remarketing lists from last year that remain open (or any at all for that matter), I recommend using the list of ideas below as thought starters.
Once you have your RLSA strategy mapped out, you should begin building lists as soon as possible to allow the audience segments sufficient time to garner members.
As mentioned, this time of year is great for e-commerce, but it’s also a very unique time in itself. Given this known variable, digital marketers should approach all campaigns with a different lens. If you have any campaigns with active ad schedules, ask yourself - do these ad schedules still set us up for success?
If you’re not sure, a good exercise is to analyze last year’s performance (especially on pivotal days like Black Friday and Cyber Monday) by the hour and date. See how your key campaigns performed throughout the hours of the day, and devise schedules that bid up during top-performing and key times of the day. Keep in mind you’re limited to how many windows of time you’d like to optimize against - so choose strategically.
Ad copy is always an important part of any digital marketing campaign, and when the competition heats up on the search engine results page it becomes even more important when you're fighting for the consumer's attention and click. In order to gain the consumer’s attention, make your ad copy compelling and tap into their emotions. Do you have a unique selling position to leverage? What special promos are you running?
Creative should be captivating enough to arrest scrolling, but also show the value your website is bringing by answering the searcher’s query. You can try to show the value that sets you apart from other advertisers by utilizing ad customizers.
If you’re running a promotion, try utilizing Countdown Ads and Promotion Extensions within your campaigns to give consumers a sense of urgency. If you also have the extra time, we recommend saving your holiday time for your family by applying labels and automated rules to these ads to schedule ads with coinciding promo periods.
One last strategy to consider would be to leverage a reactivation campaign with previous purchasers and associating relevant ad copy with these audiences to attract repeat customers.
I saw a recent Forbes article that talked about an “alarmingly” high rate of CMO turnover observed by Spencer Stuart. The piece floated a couple of ideas as to what may be driving the change - on the one hand, a potentially concerning view that CEOs may be firing CMOs more frequently, paired against a more hopeful outlook that CMOs may be moving onto bigger opportunities and challenges more often. In reality, both likely play a role and will be exacerbated by a rapidly shifting business and consumer landscape in which these CMOs must operate and deliver results. This begs the question - what are CMOs up against in 2019?
Let’s see if we can unpack some of the underlying market trends and understand what their impact is on the role of a CMO of a consumer brand in 2019. For the sake of our discovery exercise, we will begin with two questions about consumer behavior. Based on what we learn investigating them, we can begin to draw conclusions about what consumers expect, and therefore, what CMOs need to deliver to orchestrate success.
Question #1: where are consumers spending their dollars in 2019?
Coming out of the marketing and eCommerce leadership meetings at eTail East in August, a lot of discussions revolved around Amazon - it was on everyone’s mind. Market data explains why. eMarketer data suggests that Amazon is almost 50% of all eCommerce and Morgan Stanley research forecasts Amazon is in sight of a double-digit percentage of ALL retail sales. That’s absolutely staggering market share and growth! No wonder Walmart is investing so heavily to become more like Amazon.
So, based on the growth trajectory and the sheer magnitude of Amazon’s market impact, it’s clear that Amazon is winning in today’s consumer environment. Let’s dig deeper into the components of the consumer experience that are drawing shoppers to Amazon.
Question #2: what factors are causing consumers to spend their dollars on Amazon and facilitate this massive market shift?
Before doing research, I wrote down three guesses as to the biggest components of the Amazon experience that consumers are responding to: personalization, convenience, and price. Luckily enough, Statista and MarketingCharts.com have published some interesting survey results that allowed me to validate these guesses.
Statista’s research from 2017 on a sample size of just over a thousand Amazon shoppers shows the following as the biggest drivers of why consumers choose to purchase from Amazon: price, Prime benefits (including free shipping), convenience, fast shipping, and selection.
More recently, Epsilon’s survey of nearly four thousand Amazon shoppers in 2018 found the following to be the biggest factors: free shipping (a Prime benefit), price, fast shipping, convenience, and selection.
The order changed slightly from 2017 to 2018, but the top five reasons are essentially the same in both samples.
So what conclusions can we draw? Well, clearly, the recipe to compete with Amazon is pretty simple: offer low prices, a broad selection of products, and free and fast shipping, all via an incredibly convenient customer experience. If only it were so easy! Given that Walmart and its monstrous war chest of budget and resources hasn’t been able to beat Amazon, this is obviously easier said than done. And if our eTail conversations are indicative of market sentiment, this is still an elusive vision for many other marketing and eCommerce leaders as well.
I would argue that Amazon is winning in consumer experience because of an underlying framework, largely invisible to consumers, powered by data and experimentation. For example, how does Amazon offer such a large selection of products and give the perception of such low prices? The answer is that the Amazon Marketplace is an incredible venue for data collection and experimentation. Indeed, the scale and success of Amazon gives it a unique opportunity to build in its own path to expansion, growth, and even greater scale based on data.
While building an Amazon Marketplace equivalent R&D farm isn’t necessarily under the purview of most CMOs, the concept does give some valuable ideas for how to grow a business, especially given that today’s CMOs are being tasked with top-line revenue growth goals as much if not more than managing a marketing budget.
So what is a CMO to do? My first recommendation is to put on a (metaphorical) hard hat and surveyor vest and begin identifying all the various repositories that are tracking pieces of the customer journey - both online and off, as well as the data that influences how these journeys transpire. Completing this exercise produces what we call a Data Profile. Each brand and company has a unique one, but to create it, it starts with taking inventory of at least the various:
Next question - does all (or even some) of the Data Profile components get centralized somewhere? If not, there’s clearly some missed opportunity by not having the insights afforded by a single source of truth providing a more complete view of the customer journey, let alone the opportunity to drive automation based on a richer data set.
The good news is that today’s CMO oftentimes gets to wear the Chief Marketing Technologist hat too - that one is definitely a hard hat. Gone are the days of relying on a disinterested or disconnected IT department that takes quarters or even years to develop a substandard solution to yesterday’s business problems. Today, CMOs wearing their CMT hats can make quick decisions and build nimble and agile marketing stacks to collect, unify, and empower their brand’s Data Profile.
And then with the proper marketing stack, the CMO can then move forward with their next guiding principle: follow the math. Intuition, gut, and ideas are still important, but so is data-driven decision making, proper experiment design, and a culture that embraces failing fast to identify the channels, campaigns, targeting, creatives, and offers that grow revenue.
Back to Amazon. We’ve established that Amazon is one of the gold standards for consumer experience and that Amazon’s underlying infrastructure enabling data collection and experimentation is critical in achieving this success.
Who else is embracing these principles as a Marketing leader?
One recent example that stands out to me is Jim Lyski, CMO at used car mega-retailer CarMax. I had the privilege of hearing Jim speak at eTail East in August about the company’s digital transformation, including a focus on personalization, leveraging the power of data, and enabling connectivity. It was a humble discussion about how the firm, already the leading used car retailer in the country, recognized that it needed to disrupt itself. CarMax, based in Richmond, Virginia, even sent its executives and marketing teams on “safaris” to Silicon Valley to experience how startups and tech giants drive such disruption.
Jim has his hard hat on. He’s embracing that a CMO needs to be an explorer - a confident leader who relishes the fact that the future is a jungle that requires a methodical and analytical approach to tame. By doing so - via the right combination of people, technology, partnerships, and vision - there is a chance to engage with consumers in a transformational way.
Is CarMax on track to become the Amazon of used car buying? Time will tell. But kudos to Jim for bringing the right mindset to the table.
“Can we spend $30,000 by the end of June? $40,000? 100,000?!”
“How many impressions can we get with $75,000 for a campaign that’s targeting one zip code in North Dakota?!”
Media buyers and planners field these types of questions regularly, whether they’re managing ads for someone else or for their own brand.
As stressful as these questions can be, determining a campaign’s potential reach and scale doesn’t have to be a guessing game! Forecasting tools equip media buyers with the data they need to plan campaigns with confidence.
What is Forecasting?
Forecasting is a strategic media buying tool that analyzes data to generate predictions based on how a campaign is set-up. It provides information about projected spend and insight into how many impressions can be won, based on how a tactic has been set up.
Why Use Forecasting?
With forecasting, users are empowered to:
Forecasting with Basis
Powered by a proprietary algorithm, Basis’ forecasting technology generates predictions based on how each individual campaign is set-up. Our feature analyzes billions of impressions each day, allowing users to determine how many impressions are available, as well as how much they can spend, with confidence and speed.
As media buyers know, no two campaigns are identical. Market conditions shift constantly with inventory fluctuations and price changes, and audience sizes change daily as new web visitors are added to and removed from groups. Basis accounts for these and many other variations, informing users how to improve a campaign’s delivery in real-time.
Basis’ forecasting tool arms you with the necessary data to answer to any campaign question that comes your way. And it doesn’t stop there—Basis accompanies users through every step of the media buying journey, from planning to payment.
Questions? Connect with us to learn more.
Hybrid metrics can seem complicated at first glance. But once you have a basic understanding, you can leverage them to assist specific types of SEM programs in experiencing more controlled success. In this post, we break down what hybrid metrics are, when to test them and how to align them with your business goals. For specific cases, understanding and correctly implementing hybrid metrics can be the key to driving improved SEM outcomes.
It’s important to keep in mind that a hybrid metric is not a fit for every program. It’s essential to only employ them when needed or you risk overcomplicating your metrics and results.
A hybrid metric is based on two or more conversion or revenue metrics that you wish to optimize towards. It’s often a combination of a higher-funnel metric that has an abundant amount of data and a lower-funnel metric that generates less data. In most cases, the higher in the funnel the metric is, the more volume and less accuracy it will have. Conversely, the lower in the funnel the metric is, the less data is available, but it is highly accurate.
This enables you to prioritize a lower-funnel metric that has scarce data by bidding towards it and the higher funnel metric. The hybrid metric gives you more control over your results by letting you pull certain levers to focus on specific parts of your conversion funnel.
“Hybrid metrics are most useful when your business goal is too low in volume to optimize towards.” Scott Brunstein, Sr. Data Analyst at QuanticMind by Centro.
In most cases, when you have enough data it makes sense to optimize towards just one metric. However, in some situations—for example, when you have complex business goals or low conversion volume—it can be valuable to approach optimization using a hybrid metric.
If you’re curious, and you’re confident you have adequate data, you can employ this general rule of thumb: if the minimum volume is double-digit conversions in a day, then you have enough data. Depending on the program and goals, the threshold can be even lower. But generally, if the data is lower than double digits, then look into leveraging a hybrid approach.
If you think your SEM program could benefit from a hybrid metric, the first step is aligning your business goals with the proposed metric. Once you do that, select a subset of your program to test it on.
If you know your business goals, you can move on to the next section as you will use your goals to determine which type of hybrid metric to test. If not, take some time to think about what you’d like your SEM program to achieve this quarter and whereabouts in the funnel you might need some additional focus.
There are two main types of hybrid metrics:
1. Various Conversion Paths: When a program has a bunch of different conversion metrics that don’t have a true revenue value or are valued differently. You can combine and weight different styles of leads such as email, phone call, items in a cart and checkouts into one hybrid metric.
Example: Email Signups + 2*Phone Calls
2. High and Low Funnel Optimization: Allows you to leverage multiple sections of the conversion funnel and optimize towards that. A good case to use this is in SEM programs with expensive products of low volume that are optimizing to conversion metrics. If you know something higher in the funnel leads to the lower funnel conversion, you can combine those two things together.
For instance, look at email leads as part of a shopping funnel. One could optimize towards leads and conversion amounts. This lets you give the algorithm more data by optimizing to something that is close to what you want. You can boost the lower funnel one by multiplying it by a constant.
Example: Hybrid Metric = Leads + (10 * Conversions).
As mentioned earlier, if you’re going down a hybrid route, it’s important to align important business goals with the metric. Creating a priority list of what you value is a good place to start. If you need help assigning values to target towards, you can derive it from historical performance.
It can take a bit of trial and error to confirm the hybrid metric that is right for your SEM program. You can focus on a higher funnel metric such as a click on a "learn more" button instead of the actual conversion.
It’s important to go through all four steps before you start testing. This allows it to be well thought out and provides a better foundation for testing, ensuring you have accurate results.
1. What Section to Test: Determine the subset of your program that you’re willing to test on.
2. Bucket Split: Perform a bucket split of that section so you have both a control and variable bucket. The buckets should be split evenly and without bias or judgment.
3. Determine the Time Period: Set a proper pre- and post- period to assess whether or not the metric of interest (sales volume or cost per sale) has improved. Ensure you control for seasonality, latency, and other external factors.
4. Defining Success: Determine how you’re going to define success before you begin. In most cases, you’d look at conversion volume and cost per acquisition. Have an idea of what you’d consider successful even if it’s a range and then you’re ready to start the test.
After your test, you have one last thing to do: fine-tune your hybrid metric. Based on the results you can change the metric as needed. Perhaps you’d like to adjust how it’s weighted or test additional parts of the funnel. Once you’ve selected the final version of your metric, it’s important to keep it up to date.
Now that you understand the fundamentals of a hybrid metric, let’s explore a fictional example together. Let’s say you’re a bookstore selling a series of books online through your website and your goal is to hit a specific number of conversions efficiently every month. You’d like to spend a certain number of dollars for someone to purchase a book from your online store.
In this example, the book store’s online book retail program is comprised of the following:
Looking at the historical data for ad clicks over the last six months or longer would help you determine a ratio of leads to sales that you can expect. You can use this to determine a hybrid metric that you can apply to all the other keywords in your account.
This example is a good candidate for a hybrid metric as there is a large number of keywords being bid on with low sales conversions. It also has two different conversion path options.
When a hybrid metric is set up correctly, it will help you bid high enough on keywords that have strong sales volume, helping shift sales to be a larger portion of your optimization strategy than leads. It will also work to reduce bidding on the keywords that drive zero to low sales. It can also help you bid on cheaper keywords that drive more sales volume.
While a hybrid metric is a good fit in this example, keep in mind they are not suitable for every program. When they are a good fit, they can be a helpful tool to optimize toward different parts of your funnel.
If you’ve made it this far, you should have a basic understanding of hybrid metrics including, the two main types, when to use them and how to test them.
The advertising industry can be a battlefield when it comes to finding opportunities for career advancement. Roles are highly competitive—and progressing with speed can be a challenging task.
In this month's episode, we found someone who beat the system (legally, of course) and worked his way up to the executive-level in just six years!
As CEO and Board Director of WPP's data practice, the Data Alliance, Anas Ghazi manages data strategy and marketing on a global scale. Listen in as we discuss his original career aspirations, dedication to harnessing the power of data, and the sacrifices he’s made to secure a meteoric rise to the top.
Our people are a large part of what makes Centro such a great place to work. We’re excited to introduce you to some of Centro’s most interesting people in our newest blog series, as they share their ‘Centro stories’ and a variety of experiences that have impacted their work and life.
As National VP of Client and Media Services at Centro, Laura Perritte helps clients achieve their business goals while providing the raving fan service that Centro is known for.
Laura has mastered the skill of delivering superior client consultation while also arming clients to embrace ad tech software to manage their own campaign needs. Read on to learn how Laura brings a human touch to an industry marked by automation.
Noor Naseer: Even the most automated software doesn’t run by itself. What is the role of a skillful media buyer in today’s market?
Laura Peritte: Technology is amazing and it’s improving every day, but humans are irreplaceable in the process of designing channel, targeting, and messaging strategy. Even the best technology requires a thoughtful media mind to make the most of it.
Machines can’t pull actionable insights and performance stories out of data sets. They also can’t foster the human connections that create strong partnerships with our clients.
NN: What does a strategic hire look like in the media services landscape?
LP: Many of the traditional media personality traits—attention to detail, curiosity, confidence, resilience—are still applicable to achieving success in the current landscape.
When we’re looking to strategically build our team, however, it’s more about the unique perspectives and experiences that individuals can bring to the table. Diversity and creativity are fundamental to growing our capabilities as a team.
NN: How do you advise your client services team to always be prepared for any client ask?
LP: I encourage my team to read the trades, attend conferences, take meetings, ask questions—and leverage each other. We have a huge team of incredibly talented media people, and the more that they connect and share with one another, the better off all our customers will be. I also tell everyone that it’s okay not to have the answer—you just need to be resourceful enough to find it!
NN: There’s a spectrum of options when it comes to managing programmatic media campaigns. Some brands and advertisers outsource their campaigns with managed services, while others utilize a digital buying platform in-house. How should a marketer assess the tier of service they need?
LP: We published a Programmatic Readiness Guide to help marketers navigate this very decision! Here’s the process we suggest:
What’s most important is knowing that things change quickly and frequently, so the best service model is one that’s agile and evolves with your needs.
NN: Knowing that software will become more automated as time goes on, why do brands and advertisers continue to utilize client services teams to manage their campaigns?
LP: I think there’s a need for a trusted ally that can guide clients through this dynamic landscape. Agencies and brands need someone to trust—and trust is built through human relationships and experiences. Technology can help facilitate all those things, but it can’t replace the human element required to achieve them.
Throughout the last decade, the professional life of the modern-day search engine marketer has unquestionably become centered around data and artificial intelligence applications. Debates and dialogues around Al subsets, machine learning, and data science, and how exactly these buzzwords affect the workings of the industry, continue to multiply in their frequency. This trend cannot be surprising, though, when taking into consideration the truly staggering amounts of data we’re creating every minute of every day, and the pace with which we’re doing so is only accelerating with the growth of the Internet of Things (IoT). With everything from clicks to swipes, tweets to likes, we are today compiling information at an unprecedented rate.
For companies, all of this data brings new opportunities. It can be utilized and exploited by marketers to develop trend recognition, attract new customers, and ultimately create previously unforeseen efficiencies in their programs. Up until just a few years ago, businesses - both large and small - were in a position to decide whether they wanted to use data to gain a competitive advantage in their respective marketplaces. Today in the world of business, where there is a constant vying and jostling for customers, data is everything and more. Executives and practitioners uncover analytical techniques to turn the data available to them into actionable insights. The more one knows about their business, the better the decision-making and performance.
The sheer power of a data-driven marketing approach has been a much-covered subject. In a study conducted by Andrew McAfee and Erik Brynjolfsson with Harvard Business Review and MIT, it was revealed that “companies in the top third of their industry in the use of data-driven decision making were, on average, 5% more productive and 6% more profitable than their competitors.” Pretty compelling numbers.
What does all this mean, then?
Do marketers need to quickly enroll in night courses covering statistical programming and computation techniques to help them explore, and decode, large data sets? Well, the answer, in short, is no. No, they don’t.
Thankfully, with this abundance of data has come the emergence of strategies and technologies that performance marketers can take advantage of to automate some of their processes and drive significantly better business outcomes. The multi-disciplinary field of data science is chief among them, empowering marketers to combine various data sets and decipher the variables in their campaigns that are having the biggest impact on performance. To paraphrase Steve Jobs, it’s like a “bicycle for the mind”; essentially helping humans increase productivity and output. As the sphere and practice of search engine marketing have matured and expanded, managing a program and making bids manually with spreadsheets has become immensely inefficient. Even the first-generation platforms that have dominated the ecosystem for years, those with legacy foundational infrastructure, are falling behind the innovative new solutions that come fully-equipped with data science techniques on a larger, more sophisticated scale.
So, just what is this magical data science?
Let’s define it as the “art of uncovering trends”. It is, of course, infinitely more complex than that once you dig under the surface, and features a blend of Bayesian statistics, predictive modeling, time-series analysis, clustering algorithms, and regression modeling to solve analytically advanced pains. And lying at the core of all that is data. Troves of the stuff.
SEM has always been about data - we can talk about the metrics we live and breathe every day: conversion rate percentages, cost-per-click (CPC), cost-per-acquisition (CPA), revenue-per-click (RPC), return-on-ad-spend (ROAS), and I could go on and on. And these are just the outcomes.
Starting at the beginning, where all this information originates, each ad click is home to an extraordinary wealth of data when taking into account modifiers such as location, time (broken itself down into time-of-day and day-of-week), and device (desktop, mobile, and tablet). Then you can throw in on top of that other existing data points like the user’s past browsing history, purchase history, age, gender, income, and a whole lot more. We’re talking about an unfathomable number of potential permutations for every one of your keywords. This raises the question of how do I parse and act on this information.
This is where data science comes into play.
Employing data science, whether that’s through a third-party platform or proprietary in-house tools, will undoubtedly lead to a direct improvement in the performance of SEM campaigns. Here’s how it creates compelling value:
Superior Audience Targeting
Every click on a paid search ad contains vast riches of information - all sorts of demographic, psychographic, and behavioral data. Through the application of data science, marketers are empowered to parse through this information to better identify the make-up of their customers and then target them with increased accuracy accordingly. Reaching the right audience, at the right time, with the right message is paramount to any prosperous SEM campaign.
A Predictor of Success
The digital footprint that customers leave behind through their day-to-day searching habits paints an accurate portrait of their wants, needs, and interests. Predictive analysis encompasses the use of data science and statistical algorithms to translate this data and segment customer behavior, which can then be used to predict the probability of a conversion, whether it’s the buying of a product or the filling in of a form. Armed with this information, marketers can bid with more accuracy and eliminate pockets of wasted spend.
Automatically Create New Keywords
One of the many branches under the data science umbrella is natural language processing (NLP). In SEM terms, NLP is most aptly used as a keyword expansion tool whereby practitioners can leverage the technology to analyze search queries, detect associated keywords, and then suggest semantically similar keywords. This helps considerably in the expansion of your portfolio and presents areas of growth that were hitherto hidden.
Unrivaled Efficiency
Every keyword in a given SEM program has a unique, optimal bid value at which it drives the highest ROAS at the lowest possible price, otherwise known as the ideal CPC. Data science has made it possible to calculate this, unlocking efficiency on a scale not previously possible with manual bidding and legacy tools. The end result? A program that automatically and programmatically adjusts bids at the individual keyword level to ensure the best investments are being realized and new opportunities are being uncovered.
Through the introduction of data science into marketing stacks across the world, SEM managers have become empowered with significantly more knowledge about the workings and intricacies of their campaigns. With that, companies in this digital age can now reach performance levels that the executives of yesteryear could only imagine. As these technologies continue to become widespread, challenges will arise, management tactics will change, and customers will demand more personalization from brands in the searching experience. The evidence is clear, though: data science trends are showing no signs of slowing down and when data science does meet SEM, advertising ROI improves quite considerably.
Centro is on a mission to unleash the potential of digital media professionals. Our product team seeks out the biggest pain points for people working in the digital media space, and customizes a Basis solution to alleviate those roadblocks and meet unique customer needs.
Some of the biggest challenges for agencies and media professionals today include:
Basis is designed to increase capabilities and income by 35%—and give media professionals their time back—up to two hours per person (Forrester, 2019)! Don’t just take our word for it—Centro commissioned Forrester Research to survey our customers and assess how Basis solves the primary challenges faced industry-wide—read the full report here.
Forrester identified and quantified key benefits of investing in Basis, including:
Forrester found two additional qualified benefits:
Centro realizes that investing in new technology is always a risk. That’s why we commissioned Forrester to create a tool that shows media teams the value Basis can provide to their specific business environments.
How does it work?
Input your information into the calculator in order to receive your financial analysis. Your information will appear in the form of a risk-adjusted three-year Net Present Value (NPV).
What are you waiting for?