1 3 Secrets to Adding Names (and Dollars) to Your Marketing Program IT S BECOME IMPERATIVE THAT MARKETERS INVEST TIME AND RESOURCES INTO BUILDING THEIR PROGRAMS BOTH ACQUIRING NEW SUBSCRIBERS AND RETAINING EXISTING ONES.
2 3 SECRETS TO ADDING NAMES (AND DOLLARS) TO YOUR MARKETING PROGRAM The value of an marketing program can t be underestimated. In addition to being a primary customer engagement tool for brands, is proving that it s effective at driving profit to companies bottom lines. Consider the following: According to the Direct Marketing Association, the return on investment for marketing is 43 cents for every dollar spent, higher than any other digital marketing tool. Ninety-two percent of marketers recently surveyed by Marketing Sherpa said either is producing or will produce positive ROI for their businesses. open and clickthrough rates are increasing, due in large part to consumers checking their on their mobile devices. According to a report from IDC and Facebook, 78 percent of people check their on their smartphones, making it the No. 1 activity performed on mobile devices. It s become imperative that marketers invest time and resources into building their programs both acquiring new subscribers and retaining existing ones. In order to get started with your acquisition efforts, there are a couple of requirements that you must meet: One, the names that you re ing must have opted in through another channel and; two, your program needs to be CAN-SPAM compliant. Once those boxes have been checked off, you can begin developing your acquisition program. 4% 3% is producing a ROI 32% marketing will eventually produce a ROI marketing is unlikely to produce a ROI. Other 60%
3 3 SECRETS TO ADDING NAMES (AND DOLLARS) TO YOUR MARKETING PROGRAM 1. IDENTIFY YOUR GOAL The first step in building an acquisition program is to map out your brand s strategy. You ll need to have answers for the following questions: Who are you targeting? Take into consideration demographics such as age, gender, income, family status, ethnicity, etc., and how they profile against your best customers. In addition, align your offer to the audience who s receiving it. The results of a well-targeted acquisition campaign are a higher deliverability rate, higher inbox placement percentage, more opens and clicks and overall better engagement. Is your data usable? Validate that the addresses you re mailing to have a heartbeat. Remove fraudulent addresses, validate your list with several ISPs to ensure that it s deliverable, and screen for spam traps and honeypots. How are you measuring success? The ability to accurately measure the effectiveness of your acquisition campaigns leads to future optimized campaigns. Metrics such as deliverability rate, open rate, clickthrough rate, and the percentage of opt-outs and complaints provide a glimpse into what s working and what s not. A deeper dive into analytics such as ROI, landing page views, subscriber engagement (who, when, what and why) and conversion rate yields a clearer picture into the impact of your acquisition efforts. THE RESULTS OF A WELL-TARGETED ACQUISITION CAMPAIGN ARE A HIGHER DELIVERABILITY RATE, HIGHER INBOX PLACEMENT PERCENTAGE, MORE OPENS AND CLICKS AND OVERALL BETTER ENGAGEMENT.
4 3 SECRETS TO ADDING NAMES (AND DOLLARS) TO YOUR MARKETING PROGRAM 2. CREATIVE THAT SELLS After determining who you re going to send your acquisition campaign to, your focus should then move to what you re going to send them. Creating an engaging message involves combining user-friendly design tactics with copy that draws readers in and entices them into action. Within your creative, there are several components of the that require special attention. They include the following: From line: Use whatever is the most identifiable to recipients, most likely your company or brand name. Subject line: Keep this brief (ideally between 40 characters to 70 characters) and personalized/relevant to the recipient. The subject line should feature a compelling call to action for the reader e.g., sign up now to receive 10 percent off your first purchase. Be careful, however, to avoid words that are potential spam trap triggers including free, save, cash, bonus, credit, earn and extra. Body: This section, the meat of your message, can be broken down into three subcategories above the fold, offer/call to action, and below the fold. Your message should be textheavy, aligning with the 80/20 rule that around 80 percent of the message should be text and 20 percent should be images. This is particularly important today, as most clients are blocking images by default, potentially leaving important content invisible to recipients. Furthermore, optimize images for use in campaigns. The smaller the file size of an image, the faster it will load. The file size of an image should generally be 25kb or smaller. In addition, use alt-text for all of your images. This backup text will display in place of the image within clients that block images. It s a good idea to test your messages in the various clients Outlook, Gmail and Yahoo Mail to see how they render before sending. Post-send, you can begin to use A/B testing to optimize engagement. Split testing subject lines, creative (e.g., the location of a call-to-action button) and format can deliver valuable insights that can be incorporated into future campaigns. Above the Fold Above the fold refers to the roughly 300 pixels to 500 pixels of vertical space clients give recipients to preview an . This prime real estate should clearly communicate your call to action, as research shows that you only a have mere 3.5 seconds to engage a recipient with your . The call to action in an acquisition campaign is to get the recipient to agree to further communication with your brand i.e., sign up for your program. You want to communicate this request as clearly as possible and in as few words as possible. Furthermore, you want a design that makes the call to action stand out to the recipient. For example, using a call-to-action button ( Sign Up Now ) in an eyecatching color often works well. Below the fold refers to the part of the message the recipient sees upon scrolling down. This portion of your message typically sees the least engagement from your recipients, especially if you front-load all the most pertinent information above the fold. However, this doesn t mean you can ignore this section. Information that can be included below the fold includes finer details about your call to action, links to your social pages and contact information, among other lesser details. Lastly, make sure to optimize all campaigns for mobile devices. With well over half of all opens now occurring on mobile devices, it s critical that your messages are easily viewed on smartphones and tablets. If they re not, recipients will delete them immediately without a second thought or, worse yet, mark them as spam, essentially dooming your acquisition efforts.
5 3 SECRETS TO ADDING NAMES (AND DOLLARS) TO YOUR MARKETING PROGRAM 3. MAKE SURE IT REACHES ITS FINAL DESTINATION With your campaign strategy defined, target audience identified and creative complete, it s time to send your campaign. With that comes one of four outcomes: a hard bounce, which occurs if the recipient s address or domain name doesn t exist or if the recipient s server has blocked delivery; a soft bounce, which can be from a recipient s mailbox being full, the server being down, the message being too large or the ISP filter blocking the message; the message is delivered to the recipient s junk mail folder; or the best possible result, the message is delivered to the recipient s inbox. There are a number of things marketers can do to increase the chances that their s are delivered to recipients inboxes. Here are some best practices for your acquisition campaigns: Don t use your primary company domain; Use multiple creative for every 1 million names mailed to modify the creative footprint, helping prevent ISP filtering and, in turn, improving deliverability; Throttle the delivery of bigger campaigns during a few hours so a large volume doesn t hit the ISPs at one time; Be ready, willing and able to modify your sending strategy (e.g., offer, subject line, audience, volume) as results from recently deployed campaigns become known; Protect sending reputation and system infrastructure through full compliance with legally required practices; Respond to complaints as soon as possible; Ensure that you re CAN-SPAM compliant; Regularly clean your lists of opt-outs and hard bounces; and Only send legitimate offers. Key Takeaways s value as a digital marketing tool necessitates that brands continue to invest time and resources into growing their programs. With that in mind, keep these points in mind before you launch your next acquisition campaign: Acquisition is egalitarian and driven by how consumers react to your request for permission to communicate in the future. Planning and pre-deployment preparation requires time and expertise, but is essential to success. Analyzing the performance of campaigns post-deployment is key to optimizing engagement in future campaigns. Finding the right delivery cadence is critical to avoid your messages getting blocked by ISPs or filtered to spam/junk folders. According to a new report by Forrester Research, more consumers are reading s than ever before, and overall attitudes toward have become increasingly positive. It s up to marketers to take advantage of this opportunity.
6 6 Steps to Find Model Customers GO FROM TARGETING PEOPLE WHO MIGHT RESPOND TO FINDING PEOPLE WHO WILL RESPOND.
7 6 STEPS TO FIND MODEL CUSTOMERS GO FROM TARGETING PEOPLE WHO MIGHT RESPOND TO FINDING PEOPLE WHO WILL RESPOND It s your job to know your customers, what makes them buy and how to find more like them. The hard part of that job has always been separating the wheat from the chaff. But if your marketing budget is being tracked to sales and ROI more than ever, you just can t afford for half of it to be wasted. And even in media that aren t constrained by budget (like ) there s a price to be paid for wasting marketing touches (like being labeled a spammer). It s more important than ever to be able to target your marketing efforts not just to people who might be interested, but to the people who are most likely to be interested. The best way to do that is to use past performance to predict future behavior, and data modeling with predictive analytics is the key to that. Data modeling takes into account the interaction of data elements that, in combination, allow you to identify the people on a list who are most likely to take the desired action. So stop targeting the names you happen to get, and use these techniques to target people who ll be your model customers. I KNOW HALF THE MONEY I SPEND ON ADVERTISING IS WASTED. I JUST DON T KNOW WHICH HALF. John Wannamaker
8 6 STEPS TO FIND MODEL CUSTOMERS GO FROM TARGETING PEOPLE WHO MIGHT RESPOND TO FINDING PEOPLE WHO WILL RESPOND How Data Models Help Data models can be separated into two main types and strategies: Customer Models analyze the behavior of people who have already done business with you, and Acquisition Models help you identify prospects most likely to respond to your offers. In each case, the idea is to sort the list by significant variables so you can contact a smaller subset of it to get more response. In the Lift Curve table below, the Random line represents your typical campaign, where each of the contacts made bring in roughly of the total response so to get 80% of the responses, you need to mail 80% of the list. The Wizard line is an ideal world where you could get 100% of the response by mailing just of the list (essentially mailing only the people you know will convert). In the real world, no model is going to let you get that level of response, but it helps to illustrate the idea. The Validation and Estimating lines represent what data modeling lets you do. These are the results of modeling in the real world from cases Relevate did for its clients. The Estimation line shows the results the data model predicted, the Validation line shows how that model would have performed based on those individuals reactions to previous campaigns. In short, the model shows how you can get 80% of the response with only 55% of the names, and the data validation shows that those gains were real and repeatable for the clients. While those are simple concepts, they can be applied in many ways to ensure successful campaigns. For example, customer models can be very valuable when used to identify current customers who will respond best to campaigns built to optimize: Retention Reactivation Cross-Sell Lifetime Value Retention is an essential aspect of marketing, but you downloaded this whitepaper to learn how to find new model customers, which is where acquisition models come in. Used properly, acquisition models can increase response rates in your efforts to generate new customers. This means your prospecting can be conducted more profitably, and your prospecting budget will yield more new customers. 120% % OF THE MAX EXPECTED PROFIT 100% 80% 60% 40% 20% Random Wizard Validation Estimation 0% 0% 5% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100% % OF INITIAL POPULATION
9 6 STEPS TO FIND MODEL CUSTOMERS GO FROM TARGETING PEOPLE WHO MIGHT RESPOND TO FINDING PEOPLE WHO WILL RESPOND Acquisition Models There are generally two types of data models you can use to identify better customers. You can look at how prospects have responded to other marketing campaigns, or you can look at your existing good customers and use them to build a model that will help identify more customers like them. In each case, you re creating the model to find characteristics responders have in common that you can use to refine prospect lists and target only the segments that share those characteristics. Response Model Data set: Analyze a sample of solicitations and responses from prior campaigns. Action: Identify variables that differ between those who took the action (response) vs. those who did not. Good Customer Match Model Data set: Analyze a sample of your best customers. Action: Compare that to a sample of your list that have not yet taken the buying action to identify variables that set them apart. Step 1 - Data Input Step 2 - Data Prep Step 3 - Model Data Step 4 - Extract Samples Step 5a - Model Creation Step 5b - Model Validation Step 6 - Validate Entire Data Set Relevate s 6 Steps to Building a Great Acquisition Model At Relevate, we create these models for many of our clients, and we ve boiled the process down to six essential steps. You can use these steps to build your own acquisition model, or contact a data professional who can create it for you. 1. Gather the data set(s): If you re building a response model, this means pulling together the solicitation and response data to be modeled. If you re building a Good Customers model, identify those customers and compile the relevant data. 2. Standardize the data: Often this data comes from a variety of sources, and will need some work to prepare it for enhancement. 3. Append more data to that data: The modeling data set is then appended to the total universe provided to add more information that helps delineate how these customers and prospects behave. The data Relevate appends to these models includes hundreds of variables identifying consumer demographics (census data, lifestyle data, buying tendencies, etc.) and business firmographics (number of employees, sales volume, ethnicity code, woman-owned, Fortune rank, etc.) that allow you to build a 360-degree view of your customers. 4. Extraction: From the appended data set we extract two samples. We use the first to create the model, and the second to test the model. 5. Create the model: We typically will run through the modeling process a few times until we get a combination of variables that produce a scorecard that is both statistically strong and robust (more on this below). The resulting scorecard may only have 15 to 25 variables, but those are the variables that, when combined, will provide the best lift. Those are the variables we ll use to sort prospect lists to increase response rates. In the Lift Curve chart above, this was the Estimation line. 6. Validation: Finally, we apply the new model to the entire data set that was provided. In order to see what would have happened had we used the model in the past, we back cast it against past actual results for the model data set. This allows us to verify that the behavior we ve modeled syncs up with real-world results. In the Lift Curve chart above, this was the Validation line. When the validation line and estimation line are very close, as they are in the chart, that means the model is on target and repeatable.
10 6 STEPS TO FIND MODEL CUSTOMERS GO FROM TARGETING PEOPLE WHO MIGHT RESPOND TO FINDING PEOPLE WHO WILL RESPOND Using the Models Going back to the case examined in the Lift Curve chart above, here are the 15 variables the model identified as key contributors. The variables include some demographics and some buying behavior indicators. In this model, AGE has the highest contribution and Year of Vehicle has the lowest contribution. 18% 16% 14% 12% 8% 6% 4% Variable Contributions Chart Responder Model - Variable Contributions When scoring a data set, each individual will be assigned a point-value for each one of these variables to create a total score. The total scores can then be ranked from high propensity to respond to low propensity, and can be broken out into segments, such as increments ( deciles ) based on score. 2% 0% Age Ethnicity Total Online $ House- Hold Income Vehicle Type Dwelling Type Insurance Home Continuity Direct Responder Ownership Products Repsonse Orders Net Worth Catalog Buyers Retail Total $ Vehicle Year
11 6 STEPS TO FIND MODEL CUSTOMERS GO FROM TARGETING PEOPLE WHO MIGHT RESPOND TO FINDING PEOPLE WHO WILL RESPOND Here s what the scorecard looks like for the data used in the Lift Curve chart above. Total File Gains Report Total Sample Scored by the New Response Model Data Set Decile Total Customers Responders QTY %TTL QTY %TTL Index Cumulative QTY Cumulative %TTL 1 150,928 9% 1, % 248 1, % 2 157,679 9% 1, % 167 2, % 3 159,319 9% % 143 3, % 4 165, % 118 4, % 5 167, % 100 5, % 6 175, % 77 5, % 7 171, % 69 6, % 8 176, % 53 6, % 9 181,325 11% % 40 7, % ,226 11% % 22 7, % Total 1,688, % 7, % 100 Unscored 893,742 4,637 GRAND TOTAL 2,581,891 11,924 The top four deciles individually produce index levels greater than 100%. In this case, we would recommend the client select records in the top one or two deciles in an initial test. We would also recommend a random sample among all deciles, just to validate results in a live solicitation. If the test verifies the model is working, this list can be solicited at a much higher rate of return than unmodeled data, because you can sort it to zero-in on just those customers who are more likely to respond either because their response patterns dictate higher response, or because they already fit the model of your best customers. Conclusion John Wannamaker may not have known which half of his advertising wouldn t work, but with data modeling and predictive analytics, you can get a pretty good idea of exactly that for your own marketing. By eliminating names from the list that are less likely to respond and zeroing-in on model customers, your prospecting becomes much more efficient. If you re looking for a way to lift response rates and eliminate waste from your budget, ask your data scientist to run the models and cut to the top of the list.