All posts by Kyle Matthies
If someone asked you for stats on your retail card portfolio, would you respond with the number of accounts? Average spend per month? Or maybe you know the average revolving balance and profitability. Notice something about that list? Too many lenders think of their portfolio and customers as numbers when in reality these are individuals expressing themselves through their transactions. In an age where consumers increasingly expect customized experiences, marketing to account #5496115149251 is likely to fall on deaf ears. Credit card transaction data including bankcard, retail, and debit cards holds a wealth of information about your consumers\' tastes and preferences. Think about all the purchases you made using a credit card this past month. Did you shop at high-end retail stores or discount stores? Expensive restaurants or fast food? Did you buy new clothes for your kids? Maybe you went to the movies, or met friends at a bar. How you use your card paints a picture of who you are. The trick is turning all those numbers into insights. You may have been swept up in all the excitement around Apple’s announcement of the iPhone X in August. However, you may have overlooked the incorporation of Neural Embedding, or machine learning, as one of the most powerful features of the new phone. Experian DataLabs has developed an innovative approach to analyzing transaction data using similar techniques. Unstructured machine learning is applied and patterns begin to emerge around customer spending. The patterns are highly intuitive and give personality to what was previously an indecipherable stream of data. For example, one group may be more likely to spend on children’s clothing, child care services, and theme parks while another spends on expensive restaurants, airlines, and golf courses. If these two consumers happened to spend approximately the same each month on your card, you’d probably treat them as category. But understanding one is a young family and their other is jet setter allows you to tailor messaging, offers, and terms to their needs and use of your products. Further, you can ensure they have the best product based on their lifestyle to minimize silent attrition as their needs evolve. But it’s not just about marketing. When your latest attrition dashboard is updated, what period are you measuring? Do you analyze account closures from the previous month? Maybe a few months back? Understanding churn is important, but it’s inherently reactive and backward looking. You wouldn’t drive a car looking in the rearview mirror, would you? Experian enables clients to actively monitor the portfolio for attrition risk by analyzing usage patterns and predicting future spend. Transactions are then monitored up to daily and, when spend doesn’t occur as expected, an alert is sent so you can proactively attempt to save the account before it closes. These algorithms are finely tuned to reduce false positives that can come from seasonality or predictable gaps in spend such as only using a card at certain times during the week. Most importantly, it gives you an opportunity to manage each account and address changing customer needs instead of waiting for customers to call to cancel. So how well do you know your customers? If you’re still looking at them as numbers, it may be time to explore new capabilities that allow you to act small, no matter how large your portfolio. Transaction Data Insights brings cutting-edge machine learning capabilities to lenders of all sizes. By digging into behavioral segments and having tools to monitor and send alerts when a consumer is showing signs of attrition risk, card portfolios can suddenly treat customers like people, providing the customized experience they increasingly expect.
Many institutions take a “leap of faith” when it comes to developing prospecting strategies as it pertains to credit marketing. But effective strategies are developed from deep, analytical analysis with clearly identified objectives. They are constantly evolving – no setting and forgetting. So what are the basics to optimizing your prospecting efforts? Establish goals Unfortunately, far too many discussions begin with establishing targeting criteria before program goals are set. But this leads to confusion. Developing targeting criteria is kind of like squeezing a balloon; when you restrict one end, the other tends to expand. Imagine the effect of maximizing response rates when soliciting new loans. If no other criteria are considered, you could end up targeting high-risk individuals who cannot get approved elsewhere. Obviously, we’re not interested in increasing originations at all cost; risk must be understood as well. But this is where things get complicated. Lower-risk consumers tend to be the most coveted, get the best offers, and therefore have lower response rates and margins. Simplicity is best The US Navy developed the KISS acronym (keep it simple, stupid) in the 1960s on the philosophy that complexity increases the probability of error. This is largely true in targeting methodologies, but don’t mistake limiting complexity for simplicity. Perhaps the most simplistic approach to prescreen credit marketing is using only risk criteria to set an eligible population. Breaking a problem down to this single dimension generally results in low response rates and wasted budget. Propensity models and estimated interest rates are great tools for identifying consumers that are more likely to respond. Adding them as an additional filter to a credit-qualified population can help increase response rates. But what about ability to pay? So far we’ve considered propensity to open and risk (the latter being based on current financial obligations). Imagine a consumer with on-time payment behavior and a solid credit score who takes a loan only to be unable to meet their obligations. You certainly don’t want to extend debt that will cause a consumer to be overextended. Instead of going through costly income verification, income estimation models can assist with identifying the ability to repay the loan you are marketing. Simplicity is great, but not to the point of being one-dimensional. Take off the blindfold Even in the days of smartphones and GPS navigation, most people develop a plan before setting off on a road trip. In the case of credit marketing, this means running an account review or archive analysis. Remember that last prescreen campaign you ran? What could have happened with a more sophisticated targeting strategy? Having archive data appended to a past marketing campaign allows for “what if” retrospective analysis. What could response rates have been with a propensity tool? Could declines due to insufficient income have been reduced with estimated income? Archive data gives 20/20 hindsight to what could have been. Just like consulting a map to determine the shortest distance to a destination or the most scenic route, retrospective analysis on past campaigns allows for proactive planning for future efforts. Practice makes perfect Even with a plan, you probably still want to have the GPS running. Traffic could block your planned route or an unforeseen detour could divert you to a new path. Targeting strategies must continually be refined and monitored for changes in customer behavior. Test and control groups are essential to continued improvement of your targeting strategies. Every campaign should be analyzed against the goals and KPIs established at the start of the process. New hypotheses can be evaluated through test populations or small groups designed to identify new opportunities. Let’s say you typically target consumers in a risk range of 650-720, but an analyst spots an opportunity where consumers with a range of 625-649 with no delinquencies in the past 12 months performs nearly at the rate of the current population. A small test group could be included in the next campaign and studied to see if it should be expanded in future campaigns. Never “place bets” Assumptions are only valid when they are put to the test. Never dive into a strategy without testing your hypothesis. The final step in implementing a targeting strategy should be the easiest. If goals are clearly understood and prioritized, past campaigns are analyzed, and hypotheses are laid out with test and control groups, the targeting criteria should be obvious to everyone. Unfortunately, the conversation usually starts at this phase, which is akin to placing bets at the track. Ever notice that score breaks are discussed in round numbers? Consider the example of the 650-720 range. Why 650 and not 649 or 651? Without a test and learn methodology, targeting criteria ends up based on conventional wisdom – or worse, a guess. As you approach strategic planning season, make sure you run down these steps (in this order) to ensure success next year. Establish program goals and KPIs Balance simplicity with effectiveness Have a plan before you start Begin with an archive Learn and optimize In God we trust, all others bring data
For an industry that has grown accustomed to sustained year-over-year growth, recent trends are concerning. The automotive industry continued to make progress in the fourth quarter of 2016 as total automotive loan balances grew 8.6% over the previous year and exceeded $1 trillion. However, the positive trend is slowing and 2017 may be the first year since 2009 to see a market contraction. With interest rates on the rise and demand peaking, automotive lending will continue to become more competitive. Lenders can be successful in this environment, but must implement data-driven targeting strategies. Credit Unions Triumph Credit unions experienced the largest year-over-year growth in the fourth quarter of 2016, increasing 15% over the previous period. As lending faces increasing headwinds amid rising rates, credit unions can continue to play a greater role by offering members more competitive rates. For many consumers, a casual weekend trip to the auto mall turns into a big new purchase. Unfortunately, many get caught up in researching the vehicle and don’t think to shop for financing options until they’re in the F&I office. With approximately 25% share of total auto loan balances, credit unions have significant potential to recapture loans of existing members. Successful targeting starts with a review of your portfolio for opportunities with current members who have off-book loans that could be refinanced at a lower rate. After developing a strategy, many credit unions find success targeting these members with refinance offers. Helping members reduce monthly payments and interest expense provides an unexpected service that can deepen loyalty and engagement. But what criteria should you use to identify prospects? Target Receptive Consumers As originations continue to slow, marketing response rates will as well, leading to reduced marketing ROI. Maintaining performance is possible, but requires a proactive approach. Propensity models can help identify consumers who are more likely to respond, while estimated interest rates can provide insight on who is likely to benefit from refinance offers. Propensity models identify who is most likely to open a new trade. By focusing on these populations, you can cut a mail list in half or more while still focusing on the most viable prospects. It may be okay in a booming economy to send as many offers as possible, but as things slow down, getting more targeted can maintain campaign performance while saving resources for other projects. When it comes to recapture, consumers refinance to reduce their payment, interest rate, or both. Payments can often be reduced simply by ‘resetting’ the clock on a loan, or taking the remaining balance and resetting the term. Many consumers, however, will be aware of their current interest rate and only consider offers that reduce the rate as well. Estimated interest rates can provide valuable insight into a consumer’s current terms. By targeting those with high rates, you are more likely to make an offer that will be accepted. Successful targeting means getting the right message to the right consumers. Propensity models help identify “who” to target while estimated interest rates determine “what” to offer. Combining these two strategies will maximize results in even the most challenging markets. Lend Deeper with Trended Data Much of the growth in the auto market has been driven by relatively low-risk consumers, with more than 60% of outstanding balances rated prime and above. This means hypercompetition and great rates for the best consumers, while those in lower risk tiers are underserved. Many lenders are reluctant to compete for these consumers and avoid taking on additional risk for the portfolio. But trended data holds the key to finding consumers who are currently in a lower risk tier but carry significantly less risk than their current score suggests. In fact, historical data can provide much deeper insight on a consumer’s past use of credit. As an example, consider two consumers with the same risk score at a point in time. While they may be judged as carrying similar risk, trended data shows one has taken out two new trades in the past 6 months and has increasing utilization, while the other is consolidating and paying down balances. They may have the same risk score today, but what will the impact be on your future profitability? Most risk scores take a snapshot approach to gauging risk. While effective in general, it misses out on the nuance of consumers who are trending up or down based on recent behavior. Trended data attributes tell a deeper story and allow lenders to find underserved consumers who carry less risk than their current score suggests. Making timely offers to underserved consumers is a great way to grow your portfolio while managing risk. Uncertain Future The automotive industry has been a bright spot for the US economy for several years. It’s difficult to say what will happen in 2017, but there will likely be a continued slowing in originations. When markets get more competitive, data-driven targeting becomes even more important. Propensity models, estimated interest rates, and trended data should be part of every prescreen campaign. Those that integrate them now will likely shrug off any downturn and continue growing their portfolio by providing valuable and timely offers to their members.
When you think of criteria for prescreen credit marketing, what comes to mind? Most people will immediately discuss the risk criteria used to ensure consumers receiving the mailing will qualify for the product offered. Others mention targeting criteria to increase response rates and ROI. But if this is all you’re looking at, chances are you’re not seeing the whole picture. When it comes to building campaigns, marketers should consider the entire customer lifecycle, not just response rates. Yes, response rates drive ROI and can usually be measured within a couple months of the campaign drop. But what happens after the accounts get booked? Traditionally, marketers view what happens after origination as the responsibility of other teams. Managing delinquencies, attrition, and loyalty are fringe issues for the marketing manager, not the main focus. But more and more, marketers must expand their role in the organization by taking a comprehensive approach to credit marketing. In fact, truly successful campaigns will target consumers that build lasting relationships with the institution by using the three pillars of comprehensive credit marketing. Pillar #1: Maximize Response Rates At any point in time, most consumers have no interest in your products. You don’t have to look far to prove this out. Many marketing campaigns are lucky to achieve greater than a 1% response rate. As a result, marketers frequently leverage propensity to open models to improve results. These scores are highly effective at identifying consumers who are most likely to be receptive to your offer, while saving those that are not for future efforts. However, many stop with this single dimension. The fact is no propensity tool can pick out 100% of responders. Layering just a couple credit attributes to a propensity score allows you to swap in new consumers. Simultaneously, credit attributes can identify consumers with high propensity scores that are actually unlikely to open a new account. The net effect is even higher response rates than can be achieved by using a propensity score alone. Pillar #2: Risk Expansion Credit criteria are usually set using a risk score with some additional attributes. For example, a lender may target consumers with a credit score greater than 700 and no derogatory or delinquent accounts reported in the past 12 months. But, most of this data is based on a “snapshot” of the credit profile and ignores trends in the consumer’s use of credit. Consider a consumer who currently has a 690 credit score and has spent the past six months paying down debt. During that time, utilization has dropped from 66% to 41%, they’ve paid off and closed two trades, and balances have reduced from $21,000 to $13,000. However, if you only target consumers with a score greater than 700, this consumer would never appear on your prescreen list. Trended data helps spot how consumers use data over time. Using swap set analysis, you can expand your approval criteria without taking on the incremental risk. Being there when a consumer needs you is the first step in building long-term relationships. Pillar #3: Customer profitability and early attrition There’s more to profitability than just originating loans. What happens to your profitability assumptions when a consumer opens a loan and closes it within a few months? According to recent research by Experian, as many as 26% of prime and super-prime consumers, and 38% of near-prime consumers had closed a personal loan trade within nine months of opening. Further, nearly 32% of consumers who closed a loan early opened a new personal loan trade within a few months. Segmentation can help identify consumers who are likely to close a personal loan early, giving account management teams a head start to try and retain them. As it turns out, many consumers use personal loans as a form of revolving debt. These consumers occasionally close existing trades and open new trades to get access to more cash. Anticipating who is likely to close a loan early allows your retention team to focus on understanding their needs. If you don’t, you’re competition will take advantage through their marketing efforts. Building the strategy Building a comprehensive strategy is an iterative process. It’s critical for organizations to understand each campaign is an opportunity to learn and refine the methodology. Consistently leveraging control and test groups and new data assets will allow the process to become more efficient over time. Importantly, marketers should work closely across the organization to understand broader objectives and pain points. Credit data can be used to predict a range of future behaviors. As such, marketing managers should play a greater role as the gatekeepers to the organization’s growth.
Let’s play word association. When I say holiday season, what’s the first thing that comes to mind? Childhood memories. Connecting with family. A special dish mom used to make. Or perhaps it’s budgeting, debt and credit card spend. The holidays can be a stressful time of year for consumers, and also an important time for lenders to anticipate the aftermath of big credit card spend. According to a recent study by Experian and Edelman Intelligence: 48 percent of respondents felt thoughtful when thinking about the season 30 percent felt stressed 24 percent felt overwhelmed. Positive emotions are up across the board this year, which may be a good sign for retailers and bankcard lenders. And if emotion is an indicator of spending, 2016 is looking good. But while the holly-jolly sentiment is high, 56 percent of consumers say holiday shopping puts a strain on their finances. And, 43 percent of respondents said the stress of holiday shopping makes it difficult to enjoy the season. Regardless of stress, consumers are seeking ways to spend. Nearly half of respondents plan to use a major credit card to finance at least a portion of their holiday spending, second only to cash. With 44 percent of consumers saying they feel obligated to spend more than they can afford, it’s easy to see why credit cards are so important this time of year. Bankcard originations have fully rebounded from the recession, exceeding $104 billion in the third quarter of 2016, the highest level since the fourth quarter of 2007. While originations have rebounded, delinquency rates have remained at historic lows. The availability of credit is giving consumers more purchasing power to fund their holiday spending. But what happens next? As it turns out, many consumers resolve to consolidate all that holiday debt in the new year. Experian research shows that balance transfer activity reaches annual highs during the first quarter as consumers seek to simplify repayment and take advantage of lower interest rates. Proactive lenders can take advantage of this activity by making timely offers to consumers in need. At the same time, reactive lenders may feel the pain as balances transfer out of their portfolio. By identifying consumers who are most likely to engage in a card-to-card balance transfers, lenders can anticipate these consumer bankcard trends. The insights can then be used to acquire new customers and balances through prescreen campaigns, while protecting existing balances before they transfer out of an existing lender portfolio. With Black Friday and Cyber Monday behind us, the card balances are likely already rising. Now is the time for lenders to prepare for the January and February consolidations. Those hefty credit card statements are coming soon.
Experian estimates card-to-card consumer balance transfer activity to be between $35 and $40 billion a year, representing a sizeable opportunity for proactive lenders seeking to grow their revolving product line. This opportunity, however, is a threat for reactive lenders that only measure portfolio attrition instead of working to retain current customers. While billions of dollars are transferred every year, this activity represents only a small percentage of the total card population. And given the expense of direct marketing, lenders seeking to capitalize on and protect their portfolio from balance transfer activity must leverage data insights to make more informed decisions. Predicting a consumer’s future propensity to engage in card-to-card balance transfers starts with trended data. A credit score is a snapshot in time, but doesn’t reveal deep insights about a consumer’s past balance transfer activity. Lenders that rely only on current utilization will group large populations of balance revolvers into one bucket – and many of these individuals will have no intention of transferring to another product in the near future. Still, balance transfer activity can be identified and predicted by utilizing trended data. By analyzing the spend and payment data over time to see when one (or multiple) trade’s payment approximately matches another trade’s spend, we have the logic that suggests there has been a card-to-card transfer. What most people don’t realize is that trended data is difficult to work with. With 24 months of history on five fields, a single trade includes 120 data points. That’s 720 data points for a consumer with six trades on file and 72,000,000 for a file with 100,000 records, not to mention the other data fields in the file. It’s easy to see why even the most sophisticated organizations become paralyzed working with trended data. While teams of analysts get buried in the data, projects drag, costs swell, and eventually the world changes as rates climb and fall. By the time the analysis is complete, it must be recalibrated. But there is a solution. Experian has developed powerful predictions tools that combine past balance transfer history, historical transfer amounts, current trades carried and utilized, payments, and spend. Combined, these data fields can help identify consumers who are most likely to transfer a balance in the future. With Experian’s Balance Transfer Index the highest scoring 10 percent of consumers capture nearly 70 percent of total balance transfer dollars. Imagine the impact on ROI of reducing 90 percent of the marketing cost of your next balance transfer campaign and still reaching 70 percent of the balance transfer activity. Balance transfer activity represents a meaningful dollar opportunity for growth, but is concentrated in a small percentage of the population making predictive analytics key to success. Trended data is essential for identifying those opportunities, but financial institutions must assess their capabilities when it comes to managing the massive data attached. The good news is that regardless of financial institution size, solutions now exist to capture the analytics and provide meaningful and actionable insights to lenders of all sizes.
It’s more than mercury that will be up this summer. As temperatures climb, so do automotive sales, which often reach annual highs during the warmest months of the year. Fueled by pent-up demand coming out of the recession, historically low interest rates, and increased competition among both manufacturers and lenders, auto sales are continuing to be a bright spot in the U.S. economy. Summer sales spike According to recent research by Experian Automotive, 2015 sales of new non-luxury vehicles began rising in May and peaked in August at nearly 20 percent above the monthly average for the year. It is not surprising, given the number of notable manufacturer marketing campaigns that often air through the summer months, beginning with Memorial Day and running all the way through Labor Day weekend. The projection is that this trend will continue in 2016. Financing moves metal Financing continues to play an important role in facilitating new car sales. Experian research shows a consistent increase in the percentage of new vehicles sold with financing with the trend reaching a period high of 85.9 percent in Q4 2015, a 2.3 percent increase over the previous year. The increased financing, is due in part, to continued post-recession liquidity. As the economy has rebounded, lenders have re-emerged with attractive financing rates for buyers. In addition, captive lenders are continuing to support manufacturers with 0 percent subvention offers to increase sales. Total loan value is on the rise as well, reaching $29,551 in Q4 2015, a 4.1 percent increase over the previous year. Average MSRP is trending up too, but at a slower year-over-year rate of 3.6 percent. The slower growth in MSRP relative to total loan value is leading to increased loan-to-value ratios which reached 109.4 percent in Q4 2015. The increases in loan value and MSRP are putting pressure on monthly payment with average new vehicle payments reaching $493 per month on new loans in the fourth quarter. Seeking relief, consumers are turning to longer loan terms and leasing to maintain lower payments. As a result, average new vehicle loan terms ticked slightly higher to 67 months while lease penetration on new vehicles reached 28.9 percent, a 19 percent increase over the previous year. Leveraging the trends Timing is everything when it comes to auto lending. Direct mail remains an effective communication tool for lenders, but mass mailers without regard to response rates yield poor ROIs and put future campaigns in jeopardy. Targeting consumers who are most likely to be in the market at a point in time can increase response rates and improve overall campaign performance. Experian’s In the Market Model – Auto leverages the power of trended credit data to identify consumers that will be most receptive to an offer. By focusing on high-propensity consumers, lenders can conduct more marketing campaigns during the year with the same budget and achieve supercharged results. Context-based marketing allows lenders to tailor offers by leveraging insights on a consumer’s existing loans. Product offers can additionally be customized based on estimated interest rates, months remaining, or current loan balance on open auto loans. Targeted refinance offers can also be delivered to consumers with high interest rates or focus new-loan offers on consumers with minimal months or balance remaining on existing loans. Understanding current auto loans allows lenders to target offers that are relevant to their prospects and gain an advantage over the competition. Increases in loan-to-value (LTV) ratios at origination and longer loan terms are putting many consumers in deep negative equity positions. As a result, many consumers will not qualify for refinance offers without significant down payments leading to low underwriting conversion rates and poor customer experience. Lenders seeking to improve on these metrics should leverage Experian’s Auto Equity Model, which provides an estimate of the amount of equity a consumer has in their existing auto trades. Focusing refinance offers on consumers with negative equity, while suppressing those with deep negative positions, can help improve response rates while minimizing declines due to LTV requirements. Takeaways Lenders should be gearing up for the summer auto sales spike. Proactive strategies will allow savvy marketers to deploy capital and grow their portfolio by taking advantage of customer insight. Timing and context matter, and as auto sales trends reveal, now is the opportune time to optimize marketing efforts and capitalize on the season.
It’s more than mercury that will be up this summer. As temperatures climb, so do automotive sales, which often reach annual highs during the warmest months of the year. Fueled by pent-up demand coming out of the recession, historically low interest rates, and increased competition among both manufacturers and lenders, auto sales are continuing to be a bright spot in the U.S. economy. Summer sales spike According to recent research by Experian Automotive, 2015 sales of new non-luxury vehicles began rising in May and peaked in August at nearly 20 percent above the monthly average for the year. It is not surprising, given the number of notable manufacturer marketing campaigns that often air through the summer months, beginning with Memorial Day and running all the way through Labor Day weekend. The projection is that this trend will continue in 2016. Financing moves metal Financing continues to play an important role in facilitating new car sales. Experian research shows a consistent increase in the percentage of new vehicles sold with financing with the trend reaching a period high of 85.9 percent in Q4 2015, a 2.3 percent increase over the previous year. The increased financing, is due in part, to continued post-recession liquidity. As the economy has rebounded, lenders have re-emerged with attractive financing rates for buyers. In addition, captive lenders are continuing to support manufacturers with 0 percent subvention offers to increase sales. Total loan value is on the rise as well, reaching $29,551 in Q4 2015, a 4.1 percent increase over the previous year. Average MSRP is trending up too, but at a slower year-over-year rate of 3.6 percent. The slower growth in MSRP relative to total loan value is leading to increased loan-to-value ratios which reached 109.4 percent in Q4 2015. The increases in loan value and MSRP are putting pressure on monthly payment with average new vehicle payments reaching $493 per month on new loans in the fourth quarter. Seeking relief, consumers are turning to longer loan terms and leasing to maintain lower payments. As a result, average new vehicle loan terms ticked slightly higher to 67 months while lease penetration on new vehicles reached 28.9 percent, a 19 percent increase over the previous year. Leveraging the trends Timing is everything when it comes to auto lending. Direct mail remains an effective communication tool for lenders, but mass mailers without regard to response rates yield poor ROIs and put future campaigns in jeopardy. Targeting consumers who are most likely to be in the market at a point in time can increase response rates and improve overall campaign performance. Experian’s In the Market Model – Auto leverages the power of trended credit data to identify consumers that will be most receptive to an offer. By focusing on high-propensity consumers, lenders can conduct more marketing campaigns during the year with the same budget and achieve supercharged results. Context-based marketing allows lenders to tailor offers by leveraging insights on a consumer’s existing loans. Product offers can additionally be customized based on estimated interest rates, months remaining, or current loan balance on open auto loans. Targeted refinance offers can also be delivered to consumers with high interest rates or focus new-loan offers on consumers with minimal months or balance remaining on existing loans. Understanding current auto loans allows lenders to target offers that are relevant to their prospects and gain an advantage over the competition. Increases in loan-to-value (LTV) ratios at origination and longer loan terms are putting many consumers in deep negative equity positions. As a result, many consumers will not qualify for refinance offers without significant down payments leading to low underwriting conversion rates and poor customer experience. Lenders seeking to improve on these metrics should leverage Experian’s Auto Equity Model, which provides an estimate of the amount of equity a consumer has in their existing auto trades. Focusing refinance offers on consumers with negative equity, while suppressing those with deep negative positions, can help improve response rates while minimizing declines due to LTV requirements. Takeaways Lenders should be gearing up for the summer auto sales spike. Proactive strategies will allow savvy marketers to deploy capital and grow their portfolio by taking advantage of customer insight. Timing and context matter, and as auto sales trends reveal, now is the opportune time to optimize marketing efforts and capitalize on the season.
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