4 Tips for Using Omnichannel Data
What is omnichannel?
Omnichannel marketing is a concept of seamless, controlled user experience across the touchpoints of a customer journey. This experience happens across several or all available channels that are relevant to a buyer's journey from awareness to purchase and repurchase. It refers to the way a prospect is attracted and moved to and through a marketing funnel.
The patch to purchase was once a one or two-step process, now its all-encompassing. It can span days, weeks, or years, as well as locations, on top of all the media and marketing channels that can serve to influence decision making. And it's not exclusive to technology, you cannot discount the role of traditional channels like newspapers, magazines, mailers, and word-of-mouth in the modern omnichannel strategy.
The modern MarTech stack lets brands access customers practically at will, anywhere, and at any time, using multiple channels at once, the majority with built-in feedback loops in the form of metrics and data. So how do you get the most value from that data? How do you visualize it, report on it and make it actionable?
Apparently, these questions are difficult to answer. According to 2018 research from Dun & Bradstreet, only 56% of B2B marketers worldwide are currently creating actionable, data-driven insights. Perhaps even more striking, just one-third are currently personalizing experiences across digital and offline channels. This data suggests that there is significant room for growth for marketers to use the data available to them for more personalized and effective campaigns. What's most critical, however, is developing an understanding of how each customer touchpoint influences buyer behavior and how to tailor channel mix to nurture specific sales opportunities.
Here are four of TapClicks' best practices to optimize the use of omnichannel marketing data:
1. Eliminate Data Silos Data is at the heart of all smart marketing strategies. And it is best to have all your data in one place, on a single platform. The more you separate data into silos, for example into many separate excel spreadsheets, the more time and money you are going to waste making sense of it later. Data silos also make it difficult to move and share data, particularly when moving it from one silo to another. Data can be missed and its usefulness can be lost. Consider this scenario: a marketing team has data about which campaign brought in the most traffic. A sales team has data on the markets and cities that were most engaged. But neither is comparing data sets. This is a missed opportunity to bring this data together to generate well-informed conclusions and intelligence. Another issue with data silos is inconsistency. Storing data in different locations tends to lead to incompleteness and inaccuracies. Taking a data-first approach to organizing data into a single platform or database will help mitigate inconsistencies and also cut down on the volume of outdated or irrelevant entries.
2. Think Historically It is not uncommon to think about data in short-term timelines. Marketing planning tends to span 30-day cycles, but these small month-to-month slices also tend to lead to small insights. When you are able to store and analyze massive amounts of data, compiled over months and years instead of weeks and months, the knowledge base that you can use to inform intelligence and decision making becomes abundantly deep and increasingly precise. For organizations becoming serious about omnichannel marketing, now is the time to find a platform to help you aggregate data as far back as possible that will also serve your future needs.
3. Segment, Group, and Classify Different consumers exist in different stages of the customer journey at all times. The data available at each stage holds valuable information that marketers can use for analytical insights. Having access to a marketing cloud that helps group and classify data into stages, behaviors, or other segments can help extract intelligence to deliver valuable business insights. Utilizing a marketing cloud or a marketing operations platform allows your team to create user groups and cohorts based on key data attributes. If your marketing cloud saves historical data as well, the value is even greater as you can monitor spikes and behaviors over time to understand the success of omnichannel approaches with even greater analytical detail.This is one area where Artificial Intelligence (AI) and/or Machine Learning (ML) holds great promise. AI and ML are game-changing technologies but are only in their infancy in their marketing applications. That said, AI capabilities can help uncover nuances in data and draw connections between multiple data points that can reveal increasingly deep analytical insights.
4. Set up scalable marketing automation There are many great solutions that help marketers set up scalable marketing automation programs. Tools like Pardot, RavenTools, Megalytics, and iSpionage can help automate critical elements of marketing programs like email outreach campaigns and reporting. Marketing clouds like TapClicks also offer tools to automate client orders and workflows as well as offer data-driven comparisons and visualizations to derive analytical insights. Companies like Molio have been able to save upwards of $40K a year by leveraging some of these key enabling technologies. Overall, budgets spent on marketing analytics have grown steadily over the last three years. This trend is expected to continue as more money, time and resources are dedicated to analysis and reporting needs. However, there is still a lot of room to expand the contribution of analytics programs to campaign performance improvement. Only 40% of marketers report having the right quantitative tools to demonstrate the impact of marketing spends on performance in today's market. But as budgets increase, expect that access to analytics and reporting tools will too.With opportunities to market to omnipresent consumers abound and the number of channels ever-increasing, the importance of the data can not be understated. Analyzing, understanding, grouping, visualizing, and sharing data is key to successful omnichannel strategies. Storing data from all organizational departments in a common repository will help unleash deeper analytical understandings and provide increasingly actionable insights. Starting to apply best practices now before data accumulation gets out of hand will set up a business for future omnichannel success.