Back to Blog - by The Digilant Team

The process of analyzing digital data results is an important factor in today’s marketing arena. You have to initiate data-driven responses i.e., perfectly align your digital marketing and real-time analytics in order to keep your potential customers from simply clicking away from your site or choosing another brand. Thanks to digital channels, such as LinkedIn, Instagram, Facebook, or displays like affiliate marketing sites, emails, search ads, and more, it is now more important than ever before to properly react to data-driven responses by aligning these two marketing tools. This is a must because anything less than a combination of analytics and digital marketing will likely leave you looking for answers to your marketing problems while your competitors are stealing your customers, who are just a quick click away. Thankfully, by educating yourself on the process of digital analysis, you can improve their alignment within your overall marketing strategy.

Define Your Business Objective for Your Digital Presence

Before syncing analytics, or data, and digital marketing, you should first set a clear direction or objective for your business. In other words, what does digital success look like for your brand? Even the best point of sales tool or customer relationship management systems will only lead to success if these line up with your overall business goal. Setting a clear and concise business goal or growth goal is the first step in leveraging digital analytics as your personal goals for your brand might not be that of any other business.

Create a Metric for Success

The second step of utilizing analytics and digital marketing is creating a measurement strategy, a metric for success, knowing which metrics matter. In years past, many businesses focused only on specific metrics to define a successful digital marketing campaign. Metrics like session duration, bounce rates, or page views were given a great deal of value. While these are all performance indicators, they are not the most valuable in terms of turning the digital activity into sales or aligning analytics and digital marketing. For example, the number of leads your website generates has a greater impact on your overall customer retention and profit than merely the number of people who happened to make their way onto your page. Create a way to evaluate marketing success by crafting a measurement strategy.

Use Segmentation to Drive Action

If you really want to get the most out of your digital data, you need to begin segmentation. This means you will compartmentalize customers based on what they have in common. This will help you better understand how your customers behave and what you can do to reach them more effectively. Admittedly, this can be a bit difficult without the right tools and/or expertise, which is why it’s sometimes best to reach out to an expert to help you with this aspect of data analysis.

Optimize Your Digital Marketing Strategy

The following acronym is helpful to remember when trying to optimize data into your digital marketing strategy:

  • Define: What is the problem you are wanting to solve? How can you go about fixing it with digital data information?
  • Measure: Look for anomalies, track relevant data, pay attention to the data you are getting.
  • Analyze: Understanding what you are looking at is vital in terms of data is important. Look for patterns, correlations, purchasing habits, etc. Create a target persona.
  • Improve: Now that you have looked at the data, how can you improve your strategy to put it to use?
  • Control: Monitor your key performance indicators (which were mentioned above) to determine what you need to do to change your current strategy.

Optimizing a digital strategy at its root simply means taking the information you gathered through data gathering and putting it into action.

Aligning Data and Marketing

Creating an alliance between analytics and digital marketing is vitally important to having success in today’s ultra-competitive digital market. Too often digital analytics is simply set aside by marketing teams and not utilized properly. Thankfully, you can begin to align your data and your digital marketing strategies today.

To learn more about how to effectively use digital marketing analytics, check out our previous article: Understanding Digital Marketing Analytics.

Back to Blog - by The Digilant Team

The customer journey is constantly changing, and conversion hotspots are more important than ever. Determining your campaign’s most powerful stepping stones can be tough, however. Between geo-location apps driving local business traffic, social media, QR codes, and one-stop-shop e-commerce portals, plenty of digital marketers are left with the same question, time and time again:

Where is the traffic coming from, anyway?

Finding an Attribution Model that Suits Your Needs

When reaching out to new audiences, old consumer segments, current buyers, or expanding fan bases, it’s important to understand your marketing mix’s most effective conversion approaches. Marketing attribution analysis isn’t necessarily new, but today’s tools have completely redefined it. By making the most out of your brand’s outreach channels, you can supercharge the data derived from it. Naturally, this works the other way around, too. Optimizing the customer’s experience, channel to channel, is the full-circle achievement most marketers strive for—and endlessly so.

Your marketing mix attribution is unique to your brand. Because of this, it’s important to hone in on your brand’s unique channel access points, right off the bat. Not only will this give your marketing attribution analysis approach a boost from the beginning—but it’ll help paint a bigger picture of your all-around advertising performance:

With more knowledge comes increasingly effective marketing approaches. As your leads grow in number, and as your ROI begins to expand, those beginning ‘reference points’ will be amazing, broad-scope reference points.

The Nitty Gritty: Top Tips for Optimized Attribution

So, what are the best ways to achieve impactful insights? We know that data-driven, cross-channel analytics fuels marketing attribution, but how can we leverage a marketing budget with new directions? The attribution process can get a little complicated, and several obstacles face fledgling campaigns. Fortunately, knowing the right approaches to take, ahead of time, can make a big difference.

Check out these top attribution tips, and optimize your analytics approaches for the best results possible.

Tip One: Expand Beyond Last-Click Models

First-click and last-click attribution models are the bread and butter of cross-channel analysis: They show us where the customer’s journey begins—as well as where it ends. We can’t abandon these essential metrics, of course, but it’s wise to target the lesser-approached metrics between the two.

The last-click attribution model, here, is a great place to rethink, redefine and empower our strategy further. This attribution model assigns ‘conversion points’ to the last-known click location our customers visited. This said it doesn’t always paint a full picture. Here’s where non-direct click attribution analysis comes in.

Last non-direct click attribution assigns conversion credit to the final source which wasn’t direct traffic. If a potential shopper arrives at your website, for example—and if they click your display ad without converting—we should still keep an eye out for a return visit. If they do arrive the following day, making a purchase, we can safely credit our display ad. This may not be a conversion driven by direct traffic, but it’s a vital metric to consider: Conversions driven by direct traffic tend to stem from shoppers who’ve already seen our campaign. As such, measuring this bulk of direct traffic isn’t always the best for identifying the triggers behind them—as new triggers, more often than not, get mixed in with the old.

Tip Two: Give Linear Attribution a Shot

One of the reasons marketing attribution analysis can be overwhelming, regardless of a pre-existing campaign’s size, is the sheer number of channels to analyze. Consumers will follow paths of purchase through multiple avenues—both digital and physical. Keeping track of each one, and assigning different ‘relevancy’ weights to each, can quickly become expensive.

But what if we weighed each channel equally?

This is where linear attribution comes in: Depending on your campaign design, you may not want to weigh too heavily on your primary channel. A lot of channels contribute to your customer’s eventual destination, whether the touch points they encounter span across targeted ads, SEO-powered Google results, shared LinkedIn content or real-time offers.

The linear attribution model serves to weigh each channel equally, to pin down exactly where the customer’s journey begins, ends, changes direction, or hops across channels. If a customer finds your website via a Facebook ad, for example, they may not visit it right away. But let’s say, a few days later, organic search results direct them to your blog. From here, they begin exploring your content. Then, eventually, they convert.

In such a case, using the linear attribution method can help you analyze which channels have the biggest impact. While metrics like time and conversion rates are certainly useful, this type of attribution model goes hand-in-hand with PPC campaigns—as display ads, more often than not, contribute to the customer’s journey in some way, shape or form.

Tip Three: Keep Your Ad Spend In Mind

Speaking of PPC campaigns, it’s important to consider your ad spend. It’s one of the best ‘overall’ indicators of your current approach’s effectiveness, but it’s also one that has an incredibly long reach.

To make the most out of this metric, be sure to record your campaign on a day-to-day basis. Attribute your ad spend to different channels, primarily, with each ad’s source. By knowing whether your biggest opportunities exist alongside Facebook’s Ad Library, Google Ads, or Instagram, for example, you’ll know where to allocate your funds for better attribution.

You’ll also glean deeper insights into your channels as a whole, assisting any linear attribution and non-direct click analysis methods along the way.

Making the Most of Marking Attribution Analysis

Understandably, effective marketing attribution analysis requires powerful data tools. It also requires a good bit of upkeep, which can be a little cumbersome while managing campaigns as a whole. Fortunately, it’s still possible to set up your own attribution analysis strategy with some professional aid.

Digilant can help you create powerful attribution frameworks for growth, scaling, and success via today’s leading analytics tools and strategies. A well-established, empowered campaign is right around the corner—and we’re here to help, every step of the way. Contact us here.

Back to Blog - by The Digilant Team

In the fast-paced world of digital marketing, understanding and utilizing digital marketing analytics is essential for success. These analytics provide insights into customer behavior, marketing effectiveness, and overall campaign performance. By leveraging this data, marketers can optimize their strategies and achieve better results. This article will explore the key aspects of digital marketing analytics and how they can be effectively integrated into your marketing efforts.

What Are Digital Marketing Analytics?

Now that we have considered how to initiate an alliance between analytics and digital marketing, it’s a good idea to look deeper at the process of digital marketing analytics. In most cases, digital analytics consists of two main factors. They are:

Marketing Analytics: This information helps you understand your customers’ journey, even perhaps help you create a target customer persona.

Marketing Strategy: This factor comes into play when you use the information you obtained from marketing analytics to formulate a marketing strategy to meet that need.

Types of Digital Marketing Analytics

Understanding the different types of digital marketing analytics can help you better align your current marketing strategy based on analytics:

  1. Performance Analytics: This type of digital analytics looks at how your brand is doing in vital locations like Google and Instagram. It also tracks key performance indicators (KPIs) like average order value, revenues, and sales.
  2. Competitive Landscape Analytics: This helps you track how your competitors retain, convert, and attract customers. It’s wise to learn what is working for others within your industry so you can adopt similar successful strategies.
  3. Predictive Analytics: This type of digital analysis predicts the customer’s next move. It identifies what they want or need and then meets that need with the right message.
  4. Customer Behavior Analytics: This valuable data will tell you everything you need to know about your average customer’s online behavior, such as what they look for, where they browse, and when they are most active.

Why Bother With Digital Analytics?

To answer the question of why it’s important to make digital analytics a vital aspect of your digital marketing strategy, consider the benefits of digital analytics listed below:

  • Increases customers’ lifetime value.
  • Retains customers.
  • Delivers the right message at the right time.
  • Proactively relates to customers.
  • Identifies who your customers are so you can market to them more effectively.

In other words, it helps you optimize the data and put it to good use.

Tools for Digital Analytics

It’s worth noting that even the best digital analytics tools are pretty much worthless if you don’t put the data to use. The following are some free tools you can use to obtain important digital data:

  • Basic Social Media Analytics: Platforms like Facebook offer analytics that provide insights into who is considering your brand.
  • Google Analytics: This tool gathers valuable data that can be applied to your marketing strategy effectively.

The Importance of Digital Marketing Analytics

Creating an alliance between analytics and digital marketing is vitally important to having success in today’s ultra-competitive digital market. Too often digital analytics is simply set aside by marketing teams and not utilized properly. Thankfully, you can begin to align your data and your digital marketing strategies today. While you can put some information listed above into use on your own, your brand will have more success overall if you partner with a company that knows this business inside and out.

Digilant helps by aligning your digital marketing and your analytics to get the most out of each aspect. Contact us today to learn more and to begin creating a strategy to form a strong alliance between digital marketing and analytics.

For more insights into how you can integrate digital marketing analytics effectively, check out our next article: Integrating Analytics into Your Marketing Strategy.

Back to Blog - by Damon Crepin-Burr

The marketing industry has spilled a tremendous amount of ink discussing the ways in which artificial intelligence and machine learning are and will continue to change how marketers work, from brand strategy and creative ideation to media execution and attribution and measurement.

But that’s missing the forest for the trees. The real shift that’s underway is far more fundamental to not just what marketers do, but how they think. In the coming years, the industry is going to pivot from being one built on “look-back” analytics to one driven by “look-forward” predictive marketing.

That’s easy to say, but harder to fully comprehend. To grasp how artificial intelligence will change our industry (and our world), we first need to consider how human intelligence works.

The Questions Marketers Ask Today

Human brains are amazing at predicting the future based on the past. Today, that’s how marketers are spending their time. Our industry has spent vast time and resources developing studies, thinking frameworks, and methodologies designed to figure out the most likely business outcomes based on past experiences (i.e., data). Marketers are using these approaches to answer key questions like:

  • How can we get people to know and desire our brand?
  • How can we ensure that people can find our products in stores and online?
  • What is the right price for our product?
  • How much should we invest in this effort or campaign?
  • Who should our brand target with its ads?
  • What message will convince people to purchase our product?
  • What is the right media mix to reach the audiences that matter?

In relatively short order, marketers aren’t going to have to spend their time and brain power on such questions—because AI will do it for them.

Why AI Is Better Equipped to Answer Those Questions 

With the latest technology developments in AI, we are now reaching a point where the above predictions can be handled by artificial brains called neural networks — with similar or superior accuracy. We’re at a tipping point and about to witness a drastic change in both the marketing industry and our everyday lives.

Why? 

Our brains are slow and get tired easily, but computers don’t.

The revolution in which machines shattered past manual work requirements due to their ability to move mountains has now come to thinking. As we harness machine thinking power, our teams will evolve and restructure around AI to optimize our businesses. The rhythm of work, once based on human thinking, will completely change. The slow iterative marketing cycle that gives teams time to gather information, analyze past results, make decisions, and implement next steps will give way to an always-on environment of micro-optimizations. Marketers will pilot important variables, spend minimal time to analyze the past, and instead focus their energy on predicting the future.

Our input and output are limited, but computers’ are not.

Humans can only read, listen to, or watch a limited amount of information as input for our thought processes. Then we have to output what we think in concepts and languages that others can understand. Ultimately, the amount of useful thinking we produce is very limited. Machines, on the other hand, can ingest, process, and implement relevant output at incredible superhuman scale and speed.

Our memory is limited, but computer memory is not.

Humans during their very short lifespans can remember only a small amount of information and events, and without a lot of details. Because of our relatively shallow thought processes, we use conceptual shortcuts to guesstimate outcomes, whereas machines can refine the same prediction by processing very large amounts of data and computing a multitude of scenarios.

Manpower is expensive, but computers are not.

Humans eat, sleep, get sick, and take vacations. Sometimes they even decide suddenly to spend unproductive time with their spouses and kids — or just go surfing!  We’re expensive and not always available. That’s why we should be applying the cost of human work to areas where smart automation is not an option today, such as jobs that require long strides of coherence versus short “heavy lifting” tasks. The majority of what is perceived today as high-value work — research, strategy, creativity, media planning, ad operations, reporting and analytics — will become heavily automated and quickly a commodity. Marketers will instead spend their human power on understanding, in great detail, the needs of their businesses in order to help them apply, maintain, and optimize automation in a way that avoids its danger and drives responsible and sustainable business growth.

The Questions Marketers Will Ask Tomorrow

That brings us back to the questions that absorb a marketer’s time. Today, we’re focused on questions that require us to look back in time. Tomorrow, we’ll be applying our human predictive intelligence to new questions that will allow us to predict the future, like:

  • What should we automate or improve first with artificial intelligence?
  • What should we evolve (business models, teams, structures) to embrace this power?
  • How can we build and refine our predictive models?
  • How do we source and leverage qualitative, affordable, and relevant data?
  • How do we do all of this in a smart, secure, responsible, and sustainable way?

What’s Holding Back This Transition from Look-Back to Look-Forward Marketing? 

This transition from look-back analytics to look-forward predictive marketing? Like winter, it’s coming. But how quickly we get there will depend on a few needed elements falling into place.

First, let’s talk about money! Every transformation comes at a price, and jumping into the “AI-powered marketing era” is no exception. It takes training, talent, and software. For a smooth, successful transition, it is paramount to draft a realistic roadmap that prioritizes AI for operational efficiency. Doing so, you can quickly save — and loudly communicate to your organization — the amount of money you need to (re)inject in more ambitious transformative projects. It’s a great way to bring your CFO along for the ride: Test fast and small, allow imperfections on non-critical parts of the business, and learn what works.

Then, let’s remember that AI can’t learn to help you with a task if you’re not clear about what you want. That means we need to be putting effort toward training AI to think and act like a marketer. To date, very few companies in our industry have made the investment and taken the time to systematically and thoroughly solidify and document their ideal processes in a way that can be learned by a machine.

Likewise, given the near-unlimited capacity of AI to process information and identify patterns, access to reliable data has become more crucial than ever. The art and science of sourcing great (and affordable) data and organizing it in a way that can be leveraged by AI to gain competitive advantage will be at the forefront of our industry evolution.

Over time, our industry is going to see dramatic shifts in the type of data that fuels it. AI’s ability to extrapolate the information it is fed means we’re going to become far less dependent on the personal, deterministic data of individuals. (That’s great news on the privacy front.) Meanwhile, new types of non-marketing data are going to become relevant to predicting marketing outcomes and building plans—data sets like weather, traffic patterns, local context, event schedules, and more. AI’s ability to connect dots among seemingly unconnected elements will broaden the range of what kind of data is useful for marketers. Finally, when and where we need to increase the amount of data we need, its granularity, or even close the gap on data we don’t have, we will leverage “synthetic data,” a new breed created for machines by machines to accurately match real data.

Digilant’s Role in the AI-Driven Future of Marketing 

AI capabilities continue to grow among the Metas, Apples, Microsofts, and Googles of the world. But to truly bring the marketing industry into a transparent, sustainable, beneficial AI-driven future, we need independent players, like ISPD and Digilant, to develop neutral and honest AI models that seamlessly integrate and leverage the power of our industry giants but without any bias toward specific media or publishers. It’s imperative that we ensure that data, creativity, and media directly serve clients’ best interests, brands and agencies alike.

As a part of ISPD, Digilant’s AI-driven marketing solutions include:

  • Advanced qualitative research tools that leverage large language models (LLMs) to impersonate specific consumer personas and deep dive in their lives, behaviors, interest, and purchase decisions.
  • A groundbreaking marketing intelligence platform that accurately replicates your category consumers with synthetic data to understand how your past actions contributed to your results and to inform your future decisions with forecasts.
  • A new generation of brand health tracking that measures awareness, intent, and purchase at each category entry point through machine learning instead of lengthy cumbersome studies.

We’re committed to building the future of AI-driven marketing by serving as an independent, agnostic player that drives your business growth in an increasingly complex ecosystem of platforms, walled gardens, ad tech, and media. We’re excited to unlock a new path forward for marketers — one where our immense human capabilities are leveraged to their full potential, for the betterment of our brands, ourselves, and our world.

Back to Blog - by The Digilant Team

As marketers, we have an excess of tools available to track, store, and utilize data points throughout our marketing strategy. As of 2020, though, only about half of marketers were using digital marketing analytics services. But, of this same group, “marketing analytics and competitive insights” was voted the most critical factor in supporting their marketing strategies over the last 18 months.

From this data, it seems like we might be in a situation where marketers understand the importance of data analytics but don’t know where or don’t have the resources to get started. So, if you’re interested in how you can better incorporate digital marketing analytics services into your marketing campaigns, it begins with changing your mindset on data and data implementation. Below we’ve outlined a four-step process to ensure you acquire and utilize data analytics to its maximum potential.

Step One: Evaluate Your Data

Before we start any conversations about incorporating digital marketing analytics into marketing campaigns, it’s essential to stress that data for data’s sake is no longer the answer. Yes, we have all the data we could ever want at our fingertips. But, if this data isn’t working to improve your overall marketing strategy, it’s just a collection of numbers.

Data has the power to transform campaigns, uncover new audiences, prevent wasted media spend, and so much more. Ensure the data you collect, use, analyze, and incorporate is bringing value to your campaign strategy. Now, ask yourself, how am I using this data to better my marketing strategy? If you don’t have a good answer to that question, it might be time to rethink what data you are using.

Step Two: Contextualize Your Data

Data on its own is just a list or spreadsheet of numbers. But the key to building an effective bridge between marketing and analytics (and in turn, stronger digital marketing campaigns) is to paint a picture of what this data means for your overall strategy.

You can look at a 1.3% click-through rate and deem the campaign a success. But, what is that number saying about the consumer? What can you learn about your consumers from the numbers? Take some time to analyze. Look for patterns over the last few weeks, months, or quarters. Are there times when consumers are more or less engaged with your brand? Which tactics are lending themselves toward more successful results and supporting your KPIs? As you answer more questions such as this, a story begins to emerge. This story gives you much more insight into your consumers than merely a number.

Step Three: Follow the Data

Through this data analysis, you will most likely begin to see patterns emerge. Maybe you ran a social media campaign that led to an 8% increase in sales. Without throwing all of your eggs in one basket, lean into this tactic and continue to work on building data surrounding your paid social media campaign in this example. Test different creative formats offer various incentives. You know, from the data, that this channel is working. Now, use this data to figure out what aspects of these ads are yielding positive results.

You only realize the actual value of data as you implement findings into your future campaigns. Not only can you continue to build this channel, but you can take advantage of the learnings you gain and utilize similar tactics across other media and campaigns.

Step Four: Drive Decisions with Data

You’ve probably been in a position where you’re asked to create a year-end report. You’re pulling various data sources to showcase success stories from the year. In almost any situation, you can find the data to back up your story. But when you start incorporating digital marketing analytics services into your marketing campaigns, you’ll switch your mindset from backing your story up with data, to making decisions backed by data.

Finding Digital Marketing Analytics Services that Support Your Brand

As you begin to think more about bridging the gap between your data analytics and digital marketing, you may realize that you don’t have the internal resources for this task. A digital marketing partner with analytics solutions can help.

Digital marketing companies have the internal tools and personnel to create analytic reports that support the data-driven mindset outlined in steps one-four. They will be able to track and organize the data from all of your campaigns in one simple, organized location. Data analytics experts will then analyze this information to ensure your campaigns are running to their optimal capacity and provide strategic recommendations for future campaigns.

Digilant’s Digital Marketing Analytics Services

Digilant’s analytics services use over 140 connectors to quickly integrate advertising, media, social, e-commerce, and website platforms so you can visualize and report performance, all in one place. We understand that no two brands have the same digital advertising strategies and goals, so we offer custom-built dashboards to meet your needs.

We offer real-time reporting and access to your dashboard 24/7, which allows for a holistic, automated view of your digital marketing performance. Automated reports enable our team to pivot your media dollars to ensure success. Are you interested in learning more about incorporating Digilant’s digital marketing analytics services into your marketing campaigns? Let’s talk.

Back to Blog - by The Digilant Team

While brand health and market value are differing concepts, their connection is undeniable. Studies show that businesses with robust brand health are likely to outperform their competitors in revenue growth by 60%. In our ever-changing business landscape, a healthy brand is vital for enduring success.

So, how do you gauge the health of your brand? As mentioned in our blog post, Brand Health Tracking: Measure How Your Brand Stacks Up in the Market, brand health doesn’t have a universal definition or a one-size-fits-all measurement strategy. It’s about identifying factors that shape consumer perceptions of your products, services, and overall reputation.

7 Key Indicators to Track for Optimal Brand Health

Let’s dive into seven essential metrics that offer a starting point for evaluating your brand’s health in the marketplace.

1. Share of Voice (SOV)

Share of voice is a good first step to give advertisers a pulse on their brand’s presence and impact. It measures the percentage of content space or advertising that your brand occupies in the market overall. Simply put a brand’s organic digital footprint.

However, SOV isn’t solely a calculation of whether your voice is present in the market, it showcases if your voice is heard by consumers. As consumers are bombarded with digital noise, brands with a higher SOV are more likely to capture coveted consumer attention. Research indicates that brands with a dominant share of voice have a 23% higher likelihood of being recommended by consumers.

2. Category Funnel

The Category Funnel serves as a comprehensive tool for understanding a brand’s strengths and weaknesses at various stages of the customer’s buying journey. This journey typically encompasses several key stages: Awareness, Consideration, Preference, Purchase, and Loyalty.

By analyzing performance at each stage, brands can identify specific areas for improvement, whether it’s enhancing brand awareness, improving product positioning, or bolstering customer loyalty programs. This comprehensive approach to tracking the customer’s journey offers actionable insights, enabling brands to fine-tune their strategies and ultimately influence consumer decision-making more effectively.

3. Category Entry Points (CEPs)

Category Entry Points are the reasons, triggers, moments, or occasions when a potential customer considers buying a product in your category. These are the moments when someone is most receptive to your brand. Aligning marketing strategies and efforts with CEPs ensures your brand is top-of-mind when consumers are ready to make a purchase.

4. Competitive Market Position

No brand lives in isolation, which makes it essential to look externally at how other brands are performing in the market—and  how you stack up. Analyzing competitor strategies, strengths, and weaknesses with propel ideas that help differentiate your brand, strengthen your agility in response to market dynamics, and foster brand resilience. When analyzing the competitor landscape, it is essential to identify both direct and indirect competitors.

Direct competitors

These are companies that offer similar products and services. For example, a direct competitor of JetBlue would be other popular airlines in the United States such as American, United, and Alaska Airlines.

Indirect competitors

Companies that address the same customer needs but with different offerings are indirect competitors. In our example, indirect competitors of JetBlue would be Amtrak or Carnival Cruises.

5. Market Penetration & Strategic Opportunities

Deepening market penetration and recognizing strategic opportunities are pivotal for brands aiming to maximize their impact within their sector. Keeping a close eye on broad market trends and competitor movements is crucial for anticipating shifts in consumer behavior, enabling brands to adapt and innovate proactively.

Consider the ongoing emphasis on sustainability, a trend that cuts across all industries. Brands that successfully integrate eco-friendly practices and effectively communicate their commitment to sustainability are more likely to resonate with environmentally conscious consumers.

By conducting routine market analyses, brands can stay ahead of the curve, positioning themselves to make strategic decisions that align with evolving consumer preferences. This approach not only enhances the brand’s relevance but also uncovers potential avenues for growth and increased market presence, ensuring they fully exploit the opportunities within their marketplace.

6. Brand Strength Assessment

Brand strength encompasses the positive attributes, unique selling points, and competitive advantages that define your brand in the eyes of customers. It is a vital metric to gauge how well your brand is positioned in the competitive market.

One simple, yet effective approach for this assessment is a SWOT analysis (Strengths, Weaknesses, Opportunities, and Threats). This analysis draws insights from customer surveys, feedback analysis, and social media sentiment to provide honest and actionable data for brands. With these insights, brands can identify and amplify their strengths while addressing weaknesses, a fundamental practice for building a resilient brand capable of withstanding the tests of time.

7. Seasonality and Year over Year (YoY) Analysis

In various industries, businesses often witness fluctuating levels of customer engagement and demand throughout the calendar year. These fluctuations are crucial for understanding market dynamics. Utilizing SOV in YoY comparisons is a strategic approach to precisely identify these trends. This analytical method helps businesses pinpoint when customer engagement reaches its peak and when it declines, offering valuable insights for performance assessment.

For example, a retailer may use YoY comparisons to discern heightened customer interest during holiday seasons, reflected in increased SOV during these months. Similarly, a tourism-related business might notice a surge in engagement during summer and a decline in winter, highlighting key periods for targeted marketing efforts. These insights are vital for crafting marketing strategies that resonate with seasonal trends.

By understanding the rhythm of these fluctuations, businesses can tailor their marketing strategies more effectively. Aligning promotional activities with peak engagement periods ensures optimal resource utilization, enhancing the impact of marketing efforts. Conversely, identifying slower periods allows for strategic planning and resource conservation, maintaining a steady presence in the market. This nuanced approach, informed by YoY SOV analysis, is critical for businesses aiming to stay competitive and responsive to market dynamics, ultimately driving growth and success in their respective sectors.

Putting It All Together: The Road to a Healthier Brand

Maintaining brand health is a dynamic and multifaceted endeavor. From monitoring Share of Voice and Share of Search to understanding Category Entry Points, staying vigilant about competitors, and adapting to market trends, each aspect contributes to the overall vitality of your brand. By regularly assessing and fine-tuning these elements, your brand not only survives but thrives in the competitive landscape, forging lasting connections with consumers and ensuring long-term success.

Back to Blog - by The Digilant Team

Today’s consumer is bombarded with advertising messages from both traditional and digital media channels. The journey they are taking from their initial search for a solution to making a purchase is becoming more complex. According to digital marketing experts, 80 percent of consumers either start searching online and eventually make a purchase offline or start searching offline and purchase through online channels. Consequently, effective omnichannel engagement strategies are crucial to customer retention. Organizations that employ these strategies retain 89 percent of customers, while companies that do not only retain 33 percent.

Yet, with an omnichannel strategy, it’s more difficult for marketing managers and executives to determine which channel or advertising piece produced customer conversions. With all of the types of media and advertising customers see before they make a purchase, more than one channel has an influence. An omnichannel attribution model can help managers determine which advertising contributed to converting customers. Effective models can return data that reveals insights by campaigns, customer segments, and degrees of influence. However, an effective model will look different for each company and scenario. Here’s some tips on how to determine the best approach.

Factors to Consider

When designing an omnichannel attribution model, there are several questions you’ll need to ask and factors to keep in mind. The most important is the size of the organization. For instance, small companies may not always focus on more than one channel. Some campaigns or customer segments may be targeted with one media channel, while others are targeted with a larger scope. Medium to large companies, on the other hand, typically have the budgets to consistently use an omnichannel focus.

Small Organizations

If you’re a marketing manager or executive in a small company and you want to use a single channel, consider whether your sales cycle is short or long. While a short cycle typically concentrates on-demand generation, a longer cycle is more focused on conversions. Short cycles usually do best with a first-touch attribution model, while longer cycles are better served with a last-touch model. First-touch models credit the first point of advertising contact and last-touch models credit the last touchpoint. When using an omnichannel method, a small organization’s focus should shift from the length of the sales cycle to the growth strategy.

Medium to Large Organizations

Determining the optimal omnichannel attribution model for medium to large companies starts with asking whether there’s access to historical data. That data has to be both high-quality and in large enough quantities to be usable. Provided that type of data is unavailable, you should determine your growth strategy next. Without a defined growth strategy, a linear attribution model will be the best fit. Conservative growth strategies are best served by a time-decay model and aggressive growth fits with a position-based model. Firms that use an external vendor to collect, track, and manage historical data will find a data-driven omnichannel attribution model works well.

Types of Omnichannel Attribution Models

Data-Driven

A data-driven model is also called marketing mix modeling. This type of model works well for companies that have large amounts of historical data that can produce insights across a wide variety of digital and offline channels. Marketing mix modeling reveals how you can make your marketing budget more efficient by funneling more dollars into channels that have higher conversions. One of the advantages of this model is that it can also analyze sub-channels. Marketing mix modeling also incorporates factors external to the organization or campaign. For example, seasonal fluctuations in the weather or economic downturns can be used as inputs to determine temporary changes.

The con of using marketing mix modeling is that the data is often not uniform. As a result, your team will end up taking raw data from multiple sources and re-arranging it. Either you’ll need to restructure the data so that it’s apples to apples or make adjustments for differences. This can take your team extra time and additional help may be necessary. It is also more difficult for managers and executives to determine the non-financial performance of different media channels and make predictions for future campaigns.

Setting up a data-driven model works similarly to a weighted average formula. Let’s say your prospect’s first point of contact is an email, then a radio ad, followed by a call to a sales rep, then a store where a purchase is made. Depending upon the performance of each channel, you would assign a different percentage or weight to it. For example, the email was 30% effective, the radio ad was 20% effective, the call to the sales rep was 40% effective, and the trip to the store was 10% effective in converting the prospect.

Time-Decay, Position-Based, and Linear-Attribution

A time-decay model also assigns a percentage or weight indicating effectiveness to each channel. The difference is that the closer to conversion the channel is in the customer’s buying journey, the more weight it is given. This model can increase customer loyalty and incorporate all stages of the customer’s buying journey. However, this model tends to always place more value on channels that are nearest to conversion and less value on channels that are farthest away from conversion.

In a position-based model, equal emphasis is placed on the customer’s first and final exposure to advertising. Besides placing equal emphasis on the first and last channel the customer sees or interacts with, less weight or effectiveness is assigned to points of contact in the middle of the journey. Using the previous example from the data-driven model, you would assign 40% to the email and the store, along with 10% each to the radio ad and the sales rep. While this model helps managers focus on acquiring leads and converting them into customers, it discounts the other channels that could play a bigger role in converting prospects.

Unlike the other models, linear attribution assigns the same percentage of weight to all of the channels. This is the easiest model to work with and does not overlook any of the media channels. However, the model fails to take into account that different channels can exert various degrees of influence on prospects.

Tracking Channel Performance

Without the ability to track the performance of each channel with a unique ID or actions, assigning weights or percentages to different channels can be misleading and ineffective. Generally speaking, there are three different overarching methods to track channel performance. Those methods include using rules, paths, or multiple dimensions.

Using rules means that you first determine which actions to consider. For example, will unique last clicks be used to track channel performance? Or will calls into a service center be used? When paths are utilized, you look at the entire customer journey from the first contact to conversion. The same path or means to conversion is used to track performance across all channels. The multiple dimensions approach uses a unique ID for each prospect or customer as he or she goes through the channels to conversion. Although the path-based method can become less accurate when you attempt to apply it to specifics like keyword phrases, the multiple dimensions approach’s data can become limited to the channels converted prospects encounter.

Digilant’s Approach to Omnichannel Attribution

If all of this sounds overwhelming, know that omnichannel advertising experts like Digilant can help you build an effective strategy and model. Combining digital and offline advertising to convert prospects and grow your business can be challenging, even for the largest firms with the best resources. Digilant takes the guesswork out of the process and shortens the learning curve with data-driven approaches. We can offer full-service and self-service options, and over 500 clients trust us to aid in their omnichannel strategies.

Don’t put the fate of your omnichannel strategy at risk. Contact us for more information today.

Back to Blog - by The Digilant Team

When it comes to finding the right marketing campaign attribution for your medium-sized business, it is important to trust in a digital marketing agency that understands what strategy will provide the best results. There are no two businesses that are exactly alike, which means no two marketing strategies should be the same either. The right marketing campaign attribution can make or break your success each year. Depending on whether you need short or long sales cycles to successfully operate your business, you will find success from following any of these five strategies.

Making Campaign Attribution Models for Business With Short Sales Cycles

Short sales cycles are important to understand because your business does not have a long period of time to nurture a lead into a customer. These individuals are looking to quickly purchase a product or schedule a service. Often, these leads already understand what your business offers. Therefore, they do not need to go through extensive touchpoints of engagement to decide if they will do business with your company. Consider the follow attribution models:

1. First-Touch Attribution

As the name of this attribution implies, this strategy looks at your customer’s engagement history from the very first time they engaged with your brand in the sales cycle. Whether this first point of engagement was in-person, via email, on a social media post, or through your website, it is important to identify how each of your leads have found your company. This is an incredibly easy strategy to build and maintain because it follows the exact timeline of interaction. You can see the history of your customer’s engagement with your company and understand what actions lead to them finally making a purchase.

When you trust a digital marketing agency to build this strategy for you, you can ensure any and all automated events will be properly logged. Furthermore, you can trust that those who need to be notified about engaging with a lead are properly notified at the exact right time. You will not need to worry about losing out on a sale simply because your sales team was not notified of a customer inquiry.

2. Last-Touch Attribution

Similar to the last attribution strategy, last-touch attribution identifies the final engagement with leads before they become customers. While it is important to understand your customer’s history, it is even more important to identify trends in actions or conversations that lead to conversions. These conversions are what drive your business forward and provide you with the revenue needed to excel each year.

Fortunately, this strategy is just as easy for a digital marketing agency to build for your business. All pertinent information that needs to be logged can be done so with ease. As more leads convert into customers, your agency can provide you with detailed reports that show what made the conversion possible.

Making Campaign Attribution Models for Businesses With Long Sales Cycles

Long sales cycles require multiple touchpoints of engagement to fully nurture a lead into a paying customer. In order to reach a decision that leads to conversion, your business must understand how to nurture the lead. This process is lengthy and required detailed notes on each point of engagement.

3. U-Shaped Attribution

With U-shaped attribution, it combines some of the ideas of the first-touch and last-touch attribution strategies. Especially, this strategy provides 40 percent of credit to the first point of contact along with the last engagement that leads to conversion. The remaining 60 percent is evenly divided to the mid-touchpoints that occurred through the sales cycle. This type of strategy paints a complete picture of how media, messaging, and marketing tactics hooked, nurtured, and converted leads into customers.

By trusting a digital marketing agency to create this attribution strategy for your business, you can begin to fully understand your customer journey and fine-tune your sales cycle. There will not be a guessing game on what happened between the first point of engagement and the last touch. Rather, you will see the mid-touchpoints and be able to determine if they need to be expanded or decreased to create the most efficient sales cycle.

4. W-Shaped Attribution

A W-Shaped attribution strategy evenly distributes credit to the first, last, and mid-touchpoints. This type of strategy does still focus on the first and last points of engagement before conversion, but this strategy is important when all engagement is important for obtaining conversion. With a W-shaped strategy, you understand the points of engagement that both nurture and convert leads.

A digital marketing agency can help you identify all the various touchpoints that are apparent in your sales cycle. Once these are identified your agency can help you analyze data to determine if these touchpoints are more likely to educate or persuade your leads on your offering.

5. Time-Decay Attribution

A time-decay attribution strategy recognizes that events leading up to conversion carry more weight than events that occur earlier in the sales cycle. While gaining interest is important, the touchpoints that convert leads into customers are ultimately what increase your revenue. Therefore, more value is credited to the final events in the sales cycle.

Your digital marketing agency can help you determine which events are crucial to converting your leads in the final hour. These events are identified based on past sales, speaking with the individuals who interact with your leads, and understanding what actions your leads can complete without speaking to your company. This information is compiled and used to assign the best values to each touchpoint.

Trust In Marketing Campaign Attribution To Improve Your Sales

Whether your business follows a short or long sales cycle, you can improve your results by understanding what events are crucial for converting customers. For others, only the first or last touchpoints are important. For other businesses, understanding the mid touchpoints or the final stages of the sales cycle is what makes a difference in their sales.

Whatever model your business follows, Digilant can assist you. Please do not hesitate to contact us today to learn how we can help you understand your sales cycle and increase your conversion

Back to Blog - by The Digilant Team

The ultimate goal for any advertiser and their ad budgets is to drive awareness of and growth for their brand. While that may be true, however, it’s easy to get caught up in the granularity of managing campaigns and their performance, losing sight of the bigger picture. However, taking a step back to assess the bigger picture, like how your brand stacks up in its category and industry, can reveal valuable insights that help keep marketing and advertising initiatives on track and drive results.

The Importance of Brand Health and Measurement

Your brand’s share of search and voice is a way of measuring your brand’s health or foothold in its category. The greater your share of search the greater reach and popularity you have amongst your existing and potential customers, and a greater share of voice.

Measuring your brand’s share of search, understanding the competitive landscape, and how customers find and engage with your brand is critical to your brand’s health and growth. With intelligence that speaks to these brand health elements, you can identify your brand’s strengths and weaknesses — and those of your competition — to unlock new opportunities. Furthermore, by measuring your brand health, you can better analyze the impact of your advertising campaigns on your brand over time.

How Brand Health Tracking Can Help

Access to comprehensive data that illustrates the landscape of your brand category or industry isn’t always available — or easy to understand. However, Digilant’s Brand Health Tracking delivers digestible reporting on your brand’s health and how your brand stacks up by accessing more than:

  • 800 million domains
  • 25 billion keywords
  • 142 geo databases
  • 500 TB of raw website traffic from across the globe

While collecting, analyzing, and interpreting troves of data can demand extensive time and resources, it doesn’t have to. Brand Health Tracking simplifies the process by providing simple reporting that clearly highlights the insights and intelligence you need to back up your strategic media decisions and drive impact for your brand.

Campaign Effectiveness

As mentioned, it can be easy to get lost in the day-to-day of running campaigns and driving performance. And while individual campaigns might successfully deliver on KPIs and even campaign objectives, it’s essential to periodically assess the efficacy of your campaigns on the overall brand and, most importantly, its impact on your desired audiences. Moreover, understanding the overall potential for business growth can reveal valuable opportunities for your brand.

Improve your brand health today

Interested in learning more about Brand Health Tracking? Contact us to learn more about what Digilant’s Brand Health Tracking can do for you and your business.

Back to Blog - by The Digilant Team

Not long ago, marketers could only see their advertising data analytics after the campaign had ended, leading to a lot of wasted media spend. Today, real-time tracking gives advertisers a huge advantage. Not only can they see a campaign’s performance as it happens, but they can also draw conclusions and make immediate updates.

Perhaps one of the most significant benefits of real-time tracking is its ability to improve a company’s overall marketing ROI and cost efficiency. When you can shift and change tactics, budgets, and channels in response to patterns or problems, you have far more control and freedom over where your advertising money goes. Plus, you get better at learning when to shift budget away from or toward audiences based on the data you’re seeing.

But increased ROI isn’t the only reason to appreciate real-time tracking. Other benefits of real-time analytics include:

  • Quickly identifying when customers change their behaviors.
  • Testing and trying strategies or platforms right away without facing major risk or backlash.

Common Misconceptions About Marketing Analytics

Given all these positive outcomes, why aren’t all marketers embracing real-time tracking? Many still believe the myth that analytics is a time drain. Certainly, real-time tracking produces a lot of data. However, real-time tracking grows easier with the right tools, partners, and advisors. After some time, it becomes a habit, not a burden.

Another misconception about real-time tracking is that the data will only validate the marketing department’s expectations. This is highly unlikely because most companies don’t have all the answers prior to implementing advertising data analytics tools. Therefore, real-time tracking allows them to uncover untapped information that can lead to new campaigns, new channel testing, and new audience opportunities.

A final real-time misconception is that it’s too confusing to understand. To be sure, analytics isn’t a walk in the park. It takes proper investment and time to reap the benefits. Fortunately, having a solid analytics platform and user-friendly dashboards makes obtaining, validating, organizing, and implementing data far simpler.

Bringing Real-Time Tracking Into Your Marketing Department

If you’ve been searching for a way to refine your advertising and marketing initiatives, real-time advertising data analytics and tracking can be a true game changer. Below are four ways to make real-time tracking work in your favor.

1. Choose the right technology.

Finding the right technology is a necessity. Not all advertising data analytics platforms are created equal. You need to pick one that will support your specific business needs.

As you’re evaluating analytics tools, you’ll discover that many don’t give you the ability to update and track customer profiles and related data in real time. Additionally, some platforms make you wait too long to receive any pertinent insights or information. So be sure you’re getting accurate real-time tracking rather than near-real-time tracking. There’s a serious difference!

2. Strive to use your data to understand your audience.

Once you get your real-time tracking tool in place, you’ll begin to receive lots of data. It’s up to you to figure out how to put all that data to use. A prime suggestion is to use real-time data to complement your static data. Static data includes items like home addresses, preferences, and demographics. Real-time data lets you dive a little deeper and better understand customer habits and trends.

The more input you have regarding your customer base, the more tailored and customized you can make your ad campaign. For example, you might be launching a new product. With real-time advertising data analytics, you can see which audiences your campaign is resonating with. Then, you can invest more dollars toward similar audiences, which will move the needle of your advertising spend data in a welcome direction.

3. Leverage real-time tracking to adjust to buying patterns.

Nothing feels worse than finding out that a campaign flopped. Real-time analytics allows you to follow customers and react to changes they’re making in their buying behaviors. Rather than invest in touchpoints that aren’t impactful, you can get the most out of your marketing budget.

If you’re not sure how to make adjustments when you’re first relying on real-time tracking, talk with a trusted partner or advisor. It takes experience to know when and how to make changes that will make a difference in how leads are moving through your sales funnel. Be patient. Predictive analysis isn’t perfect, but it can help you make the most of opportunities.

4. Create personalized customer experiences based on incoming data.

Personalization is of growing importance to B2C and B2B customers. As a result, it’s a necessity for all brands. Real-time data systems deliver insights that you can use to improve your company’s customer personalization experience.

As you gather, organize, and implement real-time data from your campaigns, ask yourself how you can expand your personalization techniques. How can the data help you make content more timely, authentic, personal, and unique to individual users? Brainstorm solutions and try them out. Conducting A/B split tests in real time can net you instant feedback to inform your next moves.

Marketing in the 2020s has taken a turn for the better thanks to real-time tracking. Knowing your marketing and advertising campaigns helps you avoid blowing your budget or running down dead-end rabbit trails. You’ll gain more confidence and enjoy improved ROI, too.

Want to learn about Digilant’s real-time tracker for your business? Get in touch with our team today.