Digitally savvy consumers know there’s an abundance of choices when it comes to purchases. With high expectations, most will seek out appealing items with little regard to brand loyalty. Churn and attrition are at an all-time high.
The response for organizations sounds simple enough: Provide a consistently good, engaging customer experience, optimize it on a variety of devices and deliver it when customers want it. Why has it been so hard for organizations to do this?
The answer starts with the way companies operate on the back end. With multiple organizational silos, no online/offline data synthesis, rigid customer databases and other inflexible legacy systems, organizations only have a piecemeal view of the customer. It’s hard to take advantage of all the existing corporate customer data that’s available, much less the rich variety of external data. As a result, marketing efforts are fragmented. Communications are inconsistent and ineffective. And revenue growth is hindered.
By taking a technological approach that synchronizes marketing processes with the customer journey across multiple channels, organizations can achieve great results – in terms of revenue, customer advocacy and loyalty. First, they need to get a panoramic view of each customer. Then they can understand and anticipate customer behavior; orchestrate the next best action across any channel; and accurately measure results to inform future actions.
SAS recommends that you connect your marketing efforts with all the relevant data from customer interactions as well as back-end operations. Then, through advanced customer and marketing analytics, you can deliver an integrated, omnichannel experience and truly compelling content. By responding to your customers on their terms – right content, right time, right device – you can keep them coming back for more and raise their value to your business.
Step 1: Synchronize Marketing Processes Based on a Comprehensive Understanding of the Customer
When marketing departments, call centers, service operations and merchandisers operate independently based on their own distinct views of the customer, both customer engagement and marketing efforts suffer.
Consider a scenario where a customer’s browsing history (showing his preferences or inferred interests) is in one database while offline point-of-sale data about the customer is in another database. If these databases are not connected, there’s a good chance you will have less relevant interactions with that customer than what the customer expects. Or you may see the “echo effect,” where you reach the customer through one channel but he responds through a different one – leaving you unsure how to attribute the response or plan your next offer.
Many organizations don’t use their existing corporate data to the fullest extent. They overlook opportunities to enrich customer data with information from service records, operations or contact centers. Many also fail to use external data sufficiently, missing chances to broaden their understanding of the customer with data from social media, open data, third-party data, etc. In an ad sales scenario, these proprietary data sets can present a unique differentiator in the marketplace and enable you to create highly targeted campaigns for your advertisers.
SAS Customer Intelligence solutions provide a panoramic view of the customer by consolidating all first-, second- and third-party data. From digital data to CRM information and call center records, SAS captures, integrates and transforms disparate data sources, breaking down multiple customer data silos. Built-in data management capabilities ensure that you can use your data effectively to engage customers, and boost ad sales. Use SAS to:
- Improve data quality where the data resides, regardless of whether it’s in a marketing or operational system. SAS profiles, standardizes, monitors and verifies data without moving it, which creates significantly faster, more secure processes. So you can speed up many marketing processes to run in real time and near-real time instead of weeks and months.
- Access the data you need, no matter where it’s stored – from legacy systems to Hadoop. You can create data management rules once and reuse them, for a standard, repeatable method of improving and integrating data – without additional costs.
- Be confident that your data is reliable and ready to use for analytics, whether you’re doing segmentation, content recommendations, next best offer, retention or lifetime value scores.
- Create a panoramic view of the subscriber that connects all touch points, contact history and online/offline interactions.
Step 2: Understand Customer Behavior and Fuel Content Engagement
Content is core to enticing and keeping consumers. You can attract the right customers by optimizing your content. But it’s just as important to optimize the customer’s overall experience. Using advanced techniques like text and predictive analytics, you can improve search engine optimization (SEO) for digital content, quickly categorizing content and text mining words, phrases and topics for customers.
Beyond SEO, you can profile and segment customers based on their historical behavior, profitability and lifetime value. Through a range of predictive analytic models, including affinity analysis, response modeling and churn analysis, you’ll know whether it’s a good move to combine digital and print subscriptions. You’ll recognize which content merits a fee versus which content you can monetize without a paywall.
To keep your marketing efforts fresh, you’ll need to continually supply models with updated data as you interact with customers and prospects. For example, your models should include purchase transaction data, online data from website users, direct marketing response data and more.
Figure 1 - Decision Tree to quickly idenify variables that can best predict iPad usage and high versus low user populations (Click Image To Enlarge)
Through advanced analytics, you can use these models to predict behavior and:
- Identify how different customer segments are most likely to respond to specific content, campaigns or marketing actions. Your approach will be based on analytically driven, granular segmentation of both known and unknown customers.
- Reach the target population that’s most likely to respond positively to certain content, campaigns and other marketing activities. With predictive modeling, you can understand and predict the behavior of each targeted group.
- Improve economic outcomes using optimization to make the most of each individual customer communication. Take into account resource and budget constraints, contact policies, the likelihood of customers responding, and more.
Step 3: Automate and Synchronize Customer Engagement Across Channels
Once you’ve determined which analytics approach is best, you’ll need to automate your engagement activities with customers. SAS Marketing Automation helps you to quickly define target segments, prioritize selection rules, choose appropriate communication channels, schedule and execute campaigns, analyze results, and make adjustments to improve future campaign performance.
Use SAS to orchestrate data-driven marketing activities across all of your channels. So you’ll be able to present customers with the best, most profitable offers to keep them engaged or to win them back from competitors. Analyze – in real time – how people get to your site and what they do while there. Then present them with engaging content at precisely the right moment. Use SAS to:
- Build an omnichannel marketing environment so you can align outbound and inbound marketing tactics across all channels.
- Develop event-triggered campaign tactics to ensure timely, relevant marketing strategies.
- Know the next best action to take for each customer by incorporating analytics into your marketing execution efforts.
- Track the effectiveness of all marketing activities and monitor campaign results in real time.
- Reduce your reliance on IT for campaign creation and deployment with an easy-to-use interface.
With a complete view of the customer, a deep understanding of behavior and automated engagement efforts, you’ll be able to make decisions that resonate for customers and invigorate your marketing efforts. For example, if you know a customer checks email every Friday, you’ll send her an email on Friday – because you’ll know that’s the best way to reach her. You’ll also be able to decipher between premium content versus content that should be free. You’ll know what will hook your customers, whether they’re using your services for the second time or the hundredth time.
Today’s customers demand value and expect a consistent experience regardless of the channel or device they’re using. SAS positions you to meet these ultra-high customer expectations at every touch point.
Figure 2 - A marketing campaign response measurement dashboard (Click Image To Enlarge)
Step 4: Effectively Measure Campaign Performance and Attribution
It’s hard to understate the importance of accurate, useful measurement. Combining SAS Reporting capabilities with SAS Visual Analytics – a visualization and exploration suite built to handle big data – it’s easy to examine the effectiveness of your marketing campaigns and tactics based on your budget and success metrics. Use response attribution modeling to understand the customer’s conversion path, and to know where to assign marketing credit. Then you can create future marketing mix optimization models, test/control strategies, predictive models and marketing campaigns.
With adaptive, agile marketing, you can test your offers and content quickly, on a small scale, and nurture continually richer customer interactions. Then get rapid feedback to show you when and how to modify the customer’s experience to get the most impact. Plus, you’ll have easy access to campaign reports and dashboards so you can track and manage campaigns across all of your channels.
Figure 3 - Campaign and offer performance reports are integrated with revenue metrics and demographic indicators (Click Image To Enlarge)
A New Definition of Data-Driven Marketing
What is data-driven marketing, how can event marketers effectively use it to drive conversions, and why does it matter? For decades marketers were forced to launch campaigns while blindly relying on gut instinct and hoping for the best. That all changed with the digitization of business and an increasingly demanding and digitally connected consumer. Now more than ever, there is a greater urgency to develop data-driven marketing campaigns as organizations have come under increasing pressure to deliver results or ROI for their marketing spend. To be successful in this landscape, a modern marketing campaign must integrate a range of intelligent approaches to identify customers, segment, measure results, analyze data and build upon feedback in real time.
While almost every area in marketing has been folded into the digital marketing ecosystem, in-person events have remained elusive to today’s modern marketer. In fact, when it comes to tracking your marketing efforts and determining which channels provide the best return on investment (ROI), most marketers will agree that results from in-person events are still difficult to track:
- 69% of marketers say that tracking ROI for events is their primary challenge. (Aberdeen Group)
- Only 48% of marketers report having any event ROI metric in place (Regalix)
- 82% of marketers cannot quantify the data received from attendee interactions at their corporate events (Kissmetrics)
Indeed, events often lag behind other marketing methods by a significant gap, with the success or failure of many events based solely on anecdotal evidence instead of quantitative measurement and logic.
Furthermore, because data-driven marketing produces highly personalized, engagement-focused campaigns for everything from enterprise servers to event apps, consumers are now beginning to expect a high level of personalization with each transaction.
What is data-driven marketing?
Let’s start out by trying to develop a simple definition for a relatively complex concept and practice. Data-driven marketing captures insights and data from a prospect, analyzes and scores the prospect’s data and behavior, and then subsequently triggers marketing actions and campaigns based upon marketing analysis. An appropriate analogy is to think of data-driven marketing from the consumer side in the average online shopping experience. When you purchase an item online, data-driven marketing strategies provide recommendations of complementary products to provide a better overall experience. If you’re looking at airfare rates for your next vacation to Hawaii, a data-driven marketing approach will focus on restaurants around the island with cuisine you regularly Google, potential places to stay based on positive reviews on Facebook, visitor’s guides that reflect your online budget-hunting practices and local activities such as scuba diving, listed on your LinkedIn profile.
By comparison, when you look at data-driven marketing from the marketer’s side, you’ll find a much more complex process. As you are able to obtain and update information on the customer from secondary sources, such as social media sites and web search data, you can create an approach that is customized to their buying behavior, interests, past purchases, web searches, social media posts and similar information. In other words, this approach allows you to optimize your funnel and customize your buyer journey to that particular prospect’s needs. You can also survey prospects to obtain primary sources of data, but be aware that there is often a bias between what individuals or groups claim versus their actual behavior. For example, an event attendee who was ranting about poor service at the luncheon one day may be raving about the closing keynote, leaving you with plenty of praise on the keynote but failing to mention the luncheon on the exit survey. Once you’ve obtained the data you need to make a comprehensive group, you can divide your prospects up into the personas they fit into best. This allows you to customize and personalize your approach, timing, channel and subject matter to optimize the results for each persona group.
The problem many marketers run into at in-person events is that they often don’t have the information they need to determine how to best engage each prospect. The closest option currently available are scans that provide contact information and basic registration information. But scans don’t provide the data you need to track that prospect’s engagement before, during, and after the event to prove the event ROI that particular group of prospects has generated for your company. As an example, at a recent conference, my badge was scanned by a gentleman from a company that prints promotional items. I was looking through the items in his booth to determine if there was anything I could use for our company’s next event. Though the exhibitor could have collected further data from me at the time, it would have been at the cost of other prospects that he could not help while gathering my information. When I returned home from the event, I had several recommendations for items that didn’t meet our needs because the minimum quantity was much too high, the quality wasn’t good enough and the prices were too expensive. The company had my contact information, but didn’t know enough about me or my organization to make appropriate recommendations. A data-driven marketing approach to this in-person event would have drastically improved my experience while increasing the marketer’s Event ROI.
How does data-driven marketing improve your ROI?
If you’re still wondering how data-driven marketing can make a difference to your company, you’re not alone. Though there was a 14% increase in confidence in putting big data to work in marketing departments from 2013 to 2014, with expectations for additional growth, many marketers still don’t know how the additional data provides a solid improvement in ROI or how to use the data to their company’s best advantage. In fact, companies that have implemented data-driven marketing into their marketing toolbox and recorded the results have often seen a 10-20% improvement on their ROI. Like any tool, it must be used correctly and implemented with other tools in your kit, such as using social media data, search analytics, SEO, content targeting and developing better buyer personas.
Why does data-driven marketing make such a big difference? Using the marketing convention example above, if the company had used data-driven marketing techniques to track my information, they would have known my organization was operating on a modest budget. All these factors made their special offer on a tri-fold brochure with a minimum order of 5,000 a very bad fit. Instead of learning more about the client, the company made a suggestion based on what was popular with their clients in general, few of whom had the needs of our organization, and lost a prospective sale. A targeted campaign based on data-driven marketing would have recommended a small-minimum product order that was inexpensive, while offering additional items that would have fit well with our company’s mission.
Click Image To Enlarge