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As banks and credit unions face increasing pressure to compete with fintech innovations, peer-to-peer lenders and digital payment channels, it becomes more crucial than ever to optimize marketing spend and understand which channels provide the greatest ROI.
In our last post, we discussed several types of attribution models and determined that a fractional attribution model is a critical tool for optimizing the performance of marketing dollars. Here we will discuss the challenges of implementing a fractional attribution model, and the steps to get started.
Why Aren’t More Companies Using Fractional Attribution?
There is plenty of discussion happening within financial marketing organizations about the importance of marketing attribution. Unfortunately, several challenges are preventing these discussions from gaining any real traction. Common challenges preventing banks from implementing a successful, robust attribution strategy include:
- The “where do I start?” roadblock. As we saw in the last post, there are many options when it comes to marketing attribution. When faced with an overwhelming number of options, marketers have difficulty selecting the best approach to invest in, let alone deciding where to begin. These folks end up stuck in the same rut.
- A lack of executive-level sponsorship. The decision to make significant changes in overall organizational structure, talent and technology needs to be driven from the top, but making this leap is often hindered by competing priorities.
- Politicized corporate culture. The underlying issue here is often organizational structures that reward the performance of individual channels. When multiple departments compete to take full credit for revenue generation, those department leads are focused on their team’s profits, not the overall health of the company.
- Inconsistent logic. Offline and online channel marketers still attribute consumer behaviors separately with inconsistent attribution logic. The flawed justification that comes from this practice makes a combined attribution approach seem impossible to achieve (and compounds some of the other challenges listed above).
- Mobile-added complexity. The ability to track behaviors across various online-enabled devices is a data scientist’s dream, but the complexity of the data can be overwhelming for marketing organizations—and is sometimes perceived as more of a nightmare.
- Lack of the right skill sets and corresponding technology. Because the demand for data scientists is greater than the supply, it’s time to invest in top data scientists with a broad set of math and statistics skills and a deep understanding of the data landscape.
Fractional Attribution: How to Get Started
Executive-level sponsorship is key to making the transition to a new attribution model. When it comes to gaining executive-level sponsorship, you should stress the point that you can get a clearer picture of what the entire marketing budget is doing by spending just a small fraction of that budget. And by investing a small part of the marketing budget into a fractional attribution model, you can find 15–25 percent of ineffective spend within a few months of implementation. You’re not just getting an accurate map of where your marketing dollars are going, you’re reallocating those dollars in a much more effective manner. When put that way, the transition to a fractional attribution model becomes much more palatable.
You also need to make the shift to a more customer-centric focus and show how this will result in more profitable customer relationships. Here it will be helpful to perform an audit to assess current skill sets and technology infrastructure. Put together a detailed plan that shows how to get to a more robust attribution model with a phased approach—with clear success measures along the way to justify the next step.
Next Step: The Scenario Planning Tool
Implementing a fractional attribution model is only half of the solution; a scenario planning tool is needed to optimize marketing channel performance. With this tool, analysts and marketers can quickly run “what-if ” tests to gauge the impact of reallocating marketing spend. For example, what will happen if you move dollars from digital marketing and instead invest them in direct mail?
The end result is a more informed decision and higher returns from the marketing budget. Furthermore, this process can be used to calibrate and refine the attribution engine going forward.
To create the scenario planning tool, analysts outline a roadmap that identifies key performance indicators (KPIs) and details the overall attribution approach. The most robust attribution solutions require user-level data across multiple online and offline channels that need to be integrated and blended.
Spend Wisely with Better Attribution
The best decisions are data-driven, and in a multichannel world where the customer journey can span across several channels, robust attribution solutions will play a central role in informing marketing-spend decisions. It’s time to leverage analytics to start deriving insight from those large pools of data. A fractional attribution model and a scenario planning tool can optimize media and channel performance, helping you break down the silos at your institution—and showing you exactly where to allocate your marketing dollars.
Check out how we created 100s of assets for MYA Cosmetic Surgery’s sexy new #MYAworld campaign.
Instagram/ Facebook/ Snapchat Story – Vertical video
Things have been going great over at Son Of Steak, the brand new restaurant (and our fantastic client) in Nottingham’s Trinity Square.
We’ve been working on Son of Steak’s social media from the start, having set up their Facebook, Instagram, and Twitter channels back in March. Now the restaurant’s open and we have no secrets to keep, we thought we’d show a quick glimpse of some of our favourite pieces of content.
Over all the channels, we’ve created a social persona and tone of voice that gets across the passionate yet no-nonsense character of Son Of Steak, with short, to-the-point messaging, gorgeous assets, fun animations, and a good helping of attitude. For the whole picture, like Son Of Steak on Facebook, and follow on Twitter and Instagram.
A post shared by sonofsteak (@wearesonofsteak) on Mar 9, 2017 at 6:50am PST
Last week, we flew over to Barcelona to take part in OFFF Festival and to hear a keynote from Moving Brands Co-Founder and CCO, Jim Bull. We were also on the ground to hear what’s top of mind for some of the world’s best designers.
We were also in the right place to find out what some of the world’s best designers are thinking and doing. One thing, in particular, became clear, our digital lifestyles expose us daily to sensory overload. Our devotion to technology, with its constant bombardment of experiences and messaging, is dulling our senses.
In a world where brands are struggling to be heard, we need to harness the power of feeling to connect and encourage action.
Domestic Data Streamers opened the festival with a unique take on data – a topic we are all obsessed with. Big Data is often hailed as the answer to the world’s problems, from discovering life-saving medical treatments to, as Adobe showed us, taking the perfect selfie.
The challenge is, data doesn’t evoke many feelings. Which is a problem when we want to use it as a tool to build an argument or nudge people into action.
“The tools we have aren’t sufficient to understand and act on the amount of data we have access to.”
Domestic Data Streamers offered a simple solution: to connect, we need to find new human ways in which to present data. They showcased some exciting projects where they switched infographics for “info-experiences”. In one example, they represented data on real age and life expectancy with black and white balloons to significant effect.
By creating these simple experiences, large data sets can be made to connect with audiences more efficiently.
Similarly, Stink Studios demonstrated how they are harnessing the power of technology to create entertaining but resonating brand experiences, hoping to break apart the ‘creeping culture of sameness.’
By transforming a corner shop, they created a musical experience, sparked into life when unsuspecting customers chose Red Stripe from the chiller. What was exciting was the reaction it generated by making the end experience immersive and tactile.
New York based designer, Kelli Anderson reinforced the idea of lo-fi simplicity to create exciting experiences through the power of paper.
“I provide as little as I can, only what is necessary and sufficient. What happens between the user and the object is where the magic lives.”
What was brilliant about her projects is the surprise and delight factor inherent in her work. From her pop-out pinhole camera to her paper record player, her MO is to keep things as simple as possible, but in doing so, she sets the user up for a brilliant experience which makes you smile.
It is within these simple reactions that the power lies. By making someone feel, you can get them to act.
The post OFFF Festival 2017 Insights appeared first on Moving Brands – an independent, global creative company.
Did we mention it’s incredibly funny, too?
A lot of our conversations lately have been focused on providing the right content to the right person at the right spot in the buyer’s journey—marketing in the moment. This is not a simple task, given the explosive growth of customer data we have at our fingertips, driven by the various touch points across digital, social, mobile and traditional channels.
One of the challenges to marketing in the moment is bringing this data together across online and offline channels and across devices to identify individuals and the context in which they’re interacting with us. In other words, we need to take all of this big data we have available to us and turn it into small data—specific information that helps us to be more responsive to each individual.
It sounds complicated (and there are complicated algorithms and model training involved), but the concept is actually quite simple.
The Evolution of Matching
We are essentially talking about the evolution of matching. Anyone that works with marketing data is very familiar with this process. We’ve been associating individuals to households and contacts to businesses for decades, fixing truncations and abbreviations, filling data gaps in the customer profile, etc. The difference now is that, thanks to our partnership with Opera Solutions, makers of Signal Hub, this matching can be done across online and offline interactions, all in one platform, in the time requirements the business demands. This broadens what we know about our customers, allows us to identify them more quickly and in new ways, and improves our confidence in the match.
Your goal is to make sure you understand who your customers are, where they are in their buyer’s journey, and what needs they have so you can talk to them relevantly. For example, if you provide a content marketing platform, and you see a prospect Googling about how to manage content development, hitting your website, interacting with your social platforms, reading a Forbes article on managing a content team, etc., you can identify this prospect in your CRM and add the data to the record. Or, if the person is not in your CRM, you can save the information for later to make the connection when you are able.
Now, you know who this web visitor is and have a more accurate picture of the context in which she is interacting with your company. It’s probabilistic—you won’t know the identity of this person with 100% certainty until she self-identifies in some way—but you can have enough confidence in the match to speak to her contextually.
In this case, the data may tell you this person matches to Jane Smith at Acme Company A in your CRM. Since she last interacted with your brand, she has moved on to Widget Company B and moved up in title, acquiring a small content team. You’ll probably want to provide her with some content geared toward helping her learn about best practices in managing a content team, how to improve efficiencies in her development processes, etc. She’s not ready for, say, pricing information or case studies geared more toward helping her to evaluate specific solutions. Without the probabilistic match between your anonymous web visitor and Jane in your CRM, you would have none of this information with which to provide relevant messaging. Or, with a slow turnaround time on the data matching, you could miss the opportunity to speak to Jane when she’s actively looking for information.
Respect the Data
You might be thrilled to match an anonymous prospect with an email address (and you should be), but don’t jump the gun and email this person too soon. An email address is a valuable piece of data that will help you to match further valuable data points to the record—use it to this end. Your smart data matching does not mean it is a good idea to actually email this prospect. Remember: the goal is to be able to interact with individuals in a more human, relevant way. Emailing a prospect when he has not explicitly given you his email address is equivalent to cold calling him (ugh!), and he likely won’t appreciate it.
The same goes for other pieces of information you have gleaned about your customer. A good way to turn him off is to appear to be stalking his web browsing behavior, for example, and sending him a bunch of articles relevant to that activity. Respect the data, and use it in a way that helps your customer to achieve what he’s looking to achieve without being intrusive.
But…Hold Your Horses
This all sounds great, and you may want to jump right in. But the reality of it is, a lot of marketing organizations are not ready to implement this technology and these processes. Why? They’re not collecting the right data in the first place. This is referred to as the “sparse data” problem. There is a lot of data out there coming from many sources that, when combined, can provide us with great insights—but we’re not collecting or combining it today. Many marketers collect the obvious data points—name, email, etc.—but not all the available data points that would be useful in achieving their goals, such as geo location, browser ID, device ID, etc.
Not surprisingly, this problem can be remedied by increasing your data collection according to your specific goals—but don’t underestimate this endeavor. It’s a complex process that requires clearly-defined metrics and a strategic plan. Prioritize your data strategy, starting first with data housed or produced from internal platforms and applications, before moving on to partner and third-party data.
The whole idea of recognizing customers across devices and identifying “unknown” to “knowns” has been somewhat overcomplicated. It’s a natural struggle to understand everything that technology can do considering all the choices and what that means for marketing. At the end of the day, signals and the Signal Hub platform make it easier for us to understand more about customers, including who they are, which helps to interact with them more contextually, in the moment.
If you want to learn out more about our approach to bringing human interaction back to marketing, including building an effective data and martech ecosystem, check out the 5 Pillars of Best-in-Class Marketing.