Tag: Marketing Data and Analytics

Driving Retail Traffic and Sales for a Beauty Brand

Posted on by Coegi

The brief

Coegi created an omni-channel campaign to drive in-store retail traffic and attributable sales for a beauty client during a key sales period.

Highlights

$0.25
Cost Per Store Visit

4.6M
In-Store Conversions

Challenge

Your description here

Solution

Coegi used three core audiences to target this campaign – Eco Consumers, Millennial Moms and College Consumers. Additionally, we used high-intent holiday shopping audiences to maximize the time of year.

We activated these audiences across display and video campaigns, optimizing for reach and completion rate to drive in-store traffic. This was reinforced through retailer-specific creative to ensure shoppers knew where the brand was available. A foot traffic study was also implemented using mobile app ID data to correlate ad exposure with store visitation. 

We took a test and learn approach, using traffic and purchase data to determine top performing retail locations. We then reinforced those top stores in key geos, further building upon sales momentum. This campaign drove over 4.6 million store visits, with an average cost-per-store-visit of $0.25 across all media and millions in sales. This was highly efficient for driving brand consideration compared to the $3-7 product price point. 

Q4 sales reports indicated that the strong revenue numbers were directly tied with efficient cost-per-visit metrics. Analysis of foot traffic conversions also helped identify top markets for the brand. This campaign displayed the importance of combining advanced measurement studies and non-media data to determine the incremental impact of digital media on driving retail traffic and sales. 

Data Storytelling: How to Act on Analytics

Posted on by Jacob Amann

Data storytelling transforms brands. Take an inside look at how Coegi crafts stories with actionable recommendations for our clients by finding the human element in the numbers.

As marketers, we now have access to vast amounts of data. There’s been a major influx of analyst jobs in the last several years as a result.

But are we telling compelling stories with that data and adjusting our strategies based on the insights? If not, what’s the point?

The true value in data lies in how we use key insights to take informed actions for businesses. In other words, with data storytelling.

4 Steps to Set up Data Storytelling in Your Analytics Practice

Gather: Set up a measurement framework to capture metrics that matter most

First, set performance KPIs that ladder up to your business goals. For more information on how to do this, feel free to reference our Marketing Measurement Playbook. Then, prepare a learning agenda to determine the types of information you are looking to understand from your campaign.

Are there hypotheses you want to validate? Assumptions you want to challenge? Audience learnings you want to gather? Use the agenda to help answer these questions.

Learn: Capture and visualize data to pull key insights

Once the campaign is running, you begin to gather data: this is your “what.” Now, it’s up to you and your media partners to uncover the “why.” Look at the underlying narrative running through your data to build a meaningful story arc.

A great way to do this is by visualizing the data in a way. This method of data storytelling allows you to easily identify trends and understand performance relative to goals. Consider layering campaign data with third party data to see a holistic picture and identify outliers or interesting correlations. Look at the data from a macro lens. This helps weave the micro data points into a cohesive story makes sense to both marketers and external team members like the sales team or the executive suite.

We often talk about blending art and science in our marketing strategies – that same concept applies to data analytics. When communicating results to internal stakeholders, qualitative information with direction from quantitative data often speaks volumes for executives. But only if you tell the right story. You want to layer in context, feeling and understanding – the human emotion and behavior will amplify the data you’ve collected. Knowing the audience and tailoring your story to their point of view will help ensure the information resonates.

Brent Dykes, author of ‘Effective Data Storytelling’, says “Your data may hold tremendous amounts of potential value, but not an ounce of value can be created unless insights are uncovered and translated into actions or business outcomes”. This leads us into the next step: application.

Apply: Transform insights into actionable strategies, and repeat.

Data storytelling provides an opportunity to connect the dots between various media spend across channels and show how they work together to reach your customer when and where it mattered. If done right, it will also show areas that didn’t succeed. Those failures can guide new messaging or creative on particular channels, or the adjustment of certain tactics and spend reallocation. Additionally, it should highlight any gaps between customer touch points and eventual conversion or retention. Lay out clear, actionable steps based on analytic insights to transform your digital marketing strategy.

Refine and Repeat

Marketers create an infinite cycle of improvement through this data feedback loop. The digital ecosystem is constantly in flux. New platforms, privacy laws, consumer behavior and more, creating twists and turns in the media landscape. This process is never perfect. But, by using performance marketing data to tell your brand story, you can ensure it is always evolving and being refined. This practice minimizes media waste and allows marketers to make more informed decisions and craft winning strategies.

“Numbers have an important story to tell. They rely on you to give them a clear and convincing voice.” – Stephen Few

If you need help finding the story in your data, Coegi is here to help. Set up a discovery call with our team to explore opportunities for your brand.

Balancing the Art and Science of Advertising

Posted on by Coegi

 

Advertising may elicit thoughts of uniquely designed print ads and Super Bowl commercials; the output of creative minds with the ability to persuade consumer decisions. For some people, advertising seems to be a strictly artistic discipline when all one sees is the final creative product. In truth, the art and science of advertising must blend together in order to maximize marketing campaign results. 

“The solution to capturing consumers comes down to a sophisticated blend of art and science.”

– Paul Robson, President International at Adobe

On one end of the spectrum we have science, the known and the unknown, for the analytical and curious minds looking to uncover unique insights and trends. At the other end lies art, a subjective and ever-changing expression of unique thoughts and imagination in which there is truly never a right or wrong. There are a variety of perspectives on what the core of advertising is, when realistically both science and art’s synergy are central to achieving sustainable, successful strategy and activation. 

Why you need both art and science to build a brand

With art highly visible and science working behind the scenes, both pillars are critical to build the brand foundation. Our President, Sean Cotton, recently said that data is best used as a guide to craft engaging campaigns inspired by the numbers, keeping creative at the forefront while ensuring it is impactful with analytics. Sometimes this synergy is simple when you are working with a full-service agency. But, it is often more effective to work with separate creative and performance media agencies. As long as both sides communicate and prioritize business outcomes, the brand is set up for success.

How to optimize creative with data insights

At Coegi, we are the science fueling the art. We dig deeper into the what’s, why’s, and how’s of digital media through robust data analysis and industry research. The basis for our campaigns is research and analysis of our brands’ audiences. Then, we rely on machine learning and human intuition to optimize.

However, when it comes to strategy, it all really starts with the measurement framework.  This ensures we can understand if the research and thinking we put into action is actually impacting the brand’s bottom line. As a result, this process is not completely devoid of art. In fact, around 75% of an ad’s impact can be attributed to quality creative.

However, great creative pieces need data-driven insights to be delivered effectively. Our teams have to get creative with how and where we reach audiences to make the greatest impact. By doing so, we can better deliver solutions that make the art work harder, thus building up ROI. In essence, our strategy is our art.

Collaboration is key to success

At the end of the day, effective collaboration is at the core of the art and science of performance advertising. Communication and transparency between departments and our partners offers balance, allowing for seamless work processes and better results for clients. When this is done well, the lines between art and science begin to blur – proving that advertising isn’t black and white. It’s the molding of colors as the science and art of an agency work together to create a balanced composition paving the way for brand growth.

“The purpose of marketing is to influence the behaviors of others to bring them closer to your brand, organization, product, or service. The best way to achieve it is to strike a balance between the hard data and evidence that support the best path to take, and the human appeal and creative approach necessary to solidify its impact.”

– Eminent SEO CEO, Jenny Stradling

 

 

Why Walled Gardens Will (and Won’t) Be More Critical in the Future

Posted on by Coegi

 

As we explore the world of cookieless digital advertising, marketers will be focusing much of their attention on walled gardens with valuable first-party data. However, even walled gardens have issues we will need to navigate through in order to achieve business goals which are tangible to the financial guardians of brands.

Most analysts predict that walled gardens (in particular Google) will be the safest place to conduct audience targeted buys in 2024.  Even while Google’s DSP allows marketers to buy a lot of inventory, it is currently more limited in audio, connected TV and DOOH inventory.  These are channels where context is probably more important than the precision of the audience and where there is likely going to be a need to diversify to other advertising platforms to achieve a successful omni-channel strategy.

Using Facebook User Data

Facebook does have robust behavioral data from signed-in users; however, iOS 15 makes it more challenging to perform audience-based buys and to attribute conversions.  Some of our early campaigns showed a 15x increase in CPA within the platform, but nearly no impact on actual sales.  This means that conversion data on the Facebook platform was (and is) solely directional for most advertisers. While good for the business, this might be more challenging for marketers trying to prove their marketing is “working.”

Should You Trust the Algorithm?

The big ad tech players, and thus some agencies, will likely advise brands to ‘trust the algorithm’ even more than they have in the past, as Google, Facebook and Amazon don’t give specialists a lot of control over or insights about many aspects of their buying decisions.  Facebook in particular makes it challenging to control frequency, and DV360’s lookalike modeling is very opaque.  Against a lack of accurate measurement across each walled garden, brands and their agencies need to develop more holistic, advanced measurement frameworks.

How Will Cookie Deprecation Affect CPMs?

While scale is impacted slightly outside of Google Chrome and Android apps, there are still ample opportunities to bid for inventory in these environments.  However, with fewer buying platforms to conduct audience-based buys and fewer impressions to scale against, CPMs will likely increase, in particular on video.  This might put pressure on agencies to ‘keep the costs down’, which in turn may increase traffic from bots and fraudulent inventory.  Brands need to expect an increase in CPMs while not incentivizing a decrease in inventory quality.

A Walled Garden SWOT Analysis

Strengths – Google, Facebook, Amazon and Apple each have huge first-party data sets.  And not just in volume of users, they have robust metadata around each profile as well, from account information, purchase history and behavior.  Even if ID-based solutions grow in count, it’s possible we may not be able to append significant amounts of secondary data to each profile to be scalable for marketers.

Weaknesses – You will undoubtedly need adjustments in terms of attribution and measurement.  Even today, if you were to believe the metrics from each platform, nearly all of your automated marketing channels would have +ROI for the same purchase. Paid search, Facebook conversion ads and programmatic retargeting can’t all have a CPA of $10. They can’t produce 10,000 sales when you only sold 3,000 products. This is because each is taking credit for any time a user touches their ad. Because the walled gardens don’t share a common user profile, multi-touch attribution can be disjointed and inconsistent. It’s safe to say the methods of achieving measurement will have to change.

Opportunities – Lean into zero-, first- and second-party data in walled garden platforms, and rely less on retargeting. This allows for stronger prospecting and less reliance on audiences that were likely to “convert” anyway and, therefore, inflate marketing metrics.

Threats – Because many marketers and brands will be leaning into walled gardens, there will likely be an increase in advertising costs on these platforms. Budgets will need to increase to achieve the same scale as before.

So what does this mean?

At present, our suggestion is to lean into walled gardens for precise audience targeting. But, begin measuring success of your advertising program at a higher level.  Some examples of this include matched market tests, media mix modeling, and control vs. exposed methodologies.

Yes, this will make it more challenging to know which 50% of your marketing spend is effective. But, it’s the best solution with the reduction of transparency in algorithmic data and therefore less understanding of success from a conversion data standpoint.

This will also force marketers to start looking at the data as a whole. It’s time to get away from optimizing towards last-click and last-touch metrics. They have provided misleading signals for years.

Regarding measurement changes, advertising campaigns need to be set-up to reach business goals rather than just media metric KPIs.  To achieve this, individual channels and tactics will need to identify leading indicators to optimize toward.  Engagement rates, reach, completion rate, and measures of media effectiveness like CPM/CPC should become more of a focus rather than CPAs.

Check out our 5 Step Guide to Measuring Marketing ROI to get started:

Download Coegi’s Measurement Guide

What is the Coffeyville Effect and Why Does it Happen?

Posted on by Coegi

Coffeyville, Kansas

Have you ever seen an excessively large amount of US traffic supposedly coming from Coffeyville, Kansas in Google Analytics? This specific geolocation may even contribute the most amount of sessions worldwide. It is known as the Coffeyville Effect. 

What is the Coffeyville Effect?

Even though you may not be targeting Kansas, internet users who enable IP masking tools will report their location back as the exact geographical center of the U.S. which is Coffeyville, KS. 

This effect can also happen with some mobile devices that report back incorrectly or as “unknown”. 

Analytics and Ad Serving programs will often attribute those unknowns to Coffeyville. An example of this that you might have experienced is when your phone’s location service (such as on Google or a weather app) estimates you are in a city several hours away when you are connected to mobile data instead of home wifi. 

Is Google the Problem?

Google Analytics provides a number of geographical dimensions, such as City, Country, Continent, etc. The values for these dimensions derive automatically from the IP address of the hit. The Coffeyville Effect occurs when a location is not accessible by the data.

Google sends the IP addresses of traffic sources to a third-party data source to determine the location. If the third-party source determines the record of the visitor location is accurate, Google Analytics populates the fields with the location data. If the third-party source cannot find the location, the value of the corresponding fields will register as “(not set)” and then assigns the default location to the center of the US.

When Coffeyville, Kansas pops up as one of your traffic sources, it’s likely that this is the fault of one of the third-party data sources that Google uses, rather than Google itself. Unfortunately, Google does not disclose these data sources.

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