Today, the marketing landscape is oversaturated with advertisements from different brands vying for consumer attention. As a result, consumers now hold marketing content to a much higher standard, expecting brands to be on the right channel at the right time, with unique messaging that connects them to the products and services they need.
Now that consumers are firmly in the driver’s seat of their own experiences, it’s up to marketers to continuously adapt to the ebbs and flows of this consumer-dominated landscape. The marketers that can effectively course-correct to reflect the latest trends and shifts stand to capitalize on more opportunities and generate greater ROI. Those that can’t will miss opportunities across the marketing mix.
In order to ensure that campaigns generate consistent, long-term ROI, it’s crucial that marketers maintain the ability to recognize the current consumer and marketing trends that affect marketing outcomes. Moreover, the marketers with the capability to predict future trends and align campaign optimizations to address them will stay a step ahead of the competition and stand out of the crowd.
Agile marketing strategies backed by predictive analytics can be the secret weapon in the marketer’s toolbox that helps keep campaigns continuously optimized and a step ahead of the changing consumer landscape.
At a high-level, agile marketing is a tactical approach shared across the marketing team, that helps collectively identify high value projects while segmenting each project in a way that allows for cooperation, active measurement and continuous optimization. Put another way, agile marketing gives an organization and its teams the ability to continually identify marketing opportunities and align efforts to get the most ROI from those opportunities.
Adopting an agile strategy helps marketers directly address the modern and rapidly evolving consumer landscape. Moreover, it establishes the strategies and processes needed to ensure consistent, data-backed optimizations across the online and offline campaigns aimed at engaging consumers and moving them down the funnel.
At its core, agile marketing follows an iteration and reflection approach to campaign planning and implementation. Initially, campaigns are built in accordance with an overall objective. But instead of waiting for the campaign to end to reflect on data and adjust strategy, marketers make incremental changes to the live campaign, reflect on the data they receive on those changes, and make further changes accordingly.
With this in mind, there are several benefits to an agile marketing strategy that help both the marketing team and the campaign efforts they push to their target audiences:
Promotes a data-centric model for marketing decisions
Emphasizes responding to change over following a concrete plan
Allows for rapid micro-changes, measurement, and further change instead of major changes
Emphasizes marketing to the individual vs. the masses
Unifies departments and teams to promote collaboration
Responds quickly to campaign and market changes
Produces campaigns that can be rapidly tested and optimized long-term
Market tests a variety of alternative campaigns to find the ideal marketing mix
Justifies campaign decisions based on person-level data
Predictive analytics is the the use of data, machine learning, and measurement modeling to identify the likelihood of future shifts based on current and historical insights. In other words, predictive analytics goes a step beyond understanding what has happened by providing a data-backed assessment of what will happen in the future.
Considering that the foundation of agile marketing is rapid, data-based decision making, having the capability to collect, analyze and interpret data to make predictions on future campaign shifts can provide marketers with a serious boost to both agility and effectiveness. Specifically, predictive analytics can assist in the iteration and reflection processes found within the core of agile marketing.
For example, say the overarching campaign goal is to boost brand awareness for the organization prior to the market release of a particular product. Initially, marketers will develop the overarching campaign and subsequent marketing mix. However, during the periods of course correction and reflection (that help dictate further optimizations) predictive analytics can be used to maximize the impact of changes being made.
In the aforementioned example, say marketers noticed that target audiences were engaging more on digital and print channels than broadcast. From there, the team could use predictive analytics in lieu of aggregate measurements like media mix modeling to identify the best times to target consumers with campaign messaging.
As we’ve mentioned already, marketing success today is reliant on the ability to rapidly analyze data, interpret information, and use insights to optimize marketing efforts in-campaign. With this in mind, leveraging predictive analytics as part of an agile marketing strategy can unlock enormous potential for campaign efforts by allowing teams to make campaign optimizations that address market changes before they happen.
The following steps are key to successfully implementing agile marketing backed by predictive analytics:
At the heart of any successful marketing optimization is a marketing analytics platform. To accurately gather data that spans across online and offline campaigns, the platform needs to have the ability to gather data, correlate that data using the correct measurement models and accurately attribute that data to individual consumer engagements across the marketing mix.
Additionally, marketers should consider whether or not the platform has the capability to combine existing marketing measurements into a unified marketing measurement strategy. In doing so, marketers will be able to clearly view their impact across the online and offline channels. Moreover, they’ll be able to understand the relationship between channels and touchpoints and how they contribute to moving consumers down the sales funnel.
While the primary benefit of agile marketing is its capability to make rapid course corrections, it’s also vital to ensure that any change is backed by hard data. This is where a data-centric ethos within the organization comes into play, -- one that emphasizes the importance of informed decision-making and prioritises this over standard protocols or traditional techniques.This empowers teams to not only remain flexible to rapid change, but also arms them with statistical evidence to guide decisions toward effective campaign optimizations.
In the past, marketers could successfully rely on “spray and pray” marketing—leveraging generic campaign creative across a wide marketing mix in the hopes of reaching the right consumers. Today, consumers expect brands to provide relevant and fluid, omnichannel customer journeys.
This means that, along with the rapid “test and implement” approach of agile marketing, strategy must focus on the individual rather than the masses. This approach provides the relevant, targeted engagements consumers demand, while aligning efforts to address the unique changes each consumer introduces into the overarching campaign.
In order to ensure that campaign optimizations can address rapid changes while still measuring marketing impact at the person-level, marketers need a clear, unified view into the data that makes up their marketing mix. Unifying traditionally siloed departments like digital, ecommerce, broadcast, etc. ensures a wider access to data that can be used to accurately develop the insights needed for in-campaign optimizations.
No marketing team should blindly implement a campaign. With this in mind, the starting point for an agile campaign -- which dictates the initial creative, messaging, touchpoints and channels -- should be based on insights developed through previous, related campaigns. From there, marketing teams will have an established direction that can be used as a starting point for subsequent micro-testing, analysis and implementations.
Once the campaign is live, it’s crucial to take inventory of the touchpoints and channels that are driving the most engagement. Additionally, it’s important to identify where consumers are inside the sales funnel as they engage with the newly identified priority channels and touchpoints. This enables marketers to gain clear insights into the ideal customer journey that leads to optimized engagement and shortened sales cycles.
Today, the value of a positive, omnichannel customer experience cannot be understated. Consumers engage with up to 8 touchpoints before they’re ready to make a purchase decision, and as a result, there is plenty of opportunity for marketers to keep consumer attention…or lose it.That’s why agile marketing pays close attention to metrics that indicate whether engagements contribute positively or negatively to customer experience.
Let’s explore a few metrics that help identify the kind of customer experience a campaign is providing consumers:
Average time to conversion
Net promoter score (NPS)
At its very core, agile marketing relies on testing, gleaning insights from testing and applying changes based on insights. This means that marketing teams must continue to segment small, manageable campaign optimization tests across the marketing mixes. Keeping tests limited to small segments allows for rapid insights and subsequent optimizations that can keep up with the changes in today’s marketing landscape.
As the marketing landscape continues to quickly shift, the ability to identify these changes and address them accordingly is key to successful campaign optimization efforts. Enter agile marketing backed by predictive analytics -- a powerful combination that can help marketers effectively and consistently optimize to account for consumer changes down to the person-level.Interested in learning more about what marketing teams need for in-campaign optimization? Check out our recent eBook.
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