“Focus on your best customers.” “Go after the big fish.” “Drive greater customer profitability.”
You have probably said some version of these statements to your team or have been given such mandates by your boss. And at first glance, they are all straightforward. little deeper reveals that words like “best”, “big”, and “profitability” can be interpreted in different ways.
Customer lifetime value (CLV) is a single metric that gets rid of the ambiguity. It incorporates sales revenue with all costs associated with each product or service sold. Customers who buy low-margin products will have a lower CLV than customers who buy high-margin products. Prospects who are likely to buy your products and keep purchasing them over time have a higher CLV than a “one and done” new customer. Obviously, you want to spend more time, effort, and marketing budget and selling to high-CLV customers and prospects.
CLV is a forward-looking metric based on historical data, customer/prospect firmographics, financial modeling, and predictive data sciences. It calculates the net present value of the future profitability of each individual customer and prospect. It may be complicated but the roadmap is simple: The more CLV the better.
Calculating CLV is not an easy endeavor (or else you would have done it already). It requires a cross-functional team consisting of Finance, Sales, Marketing, IT, Operations, and Analytics professionals. These groups need to work together to:
Once you have CLV calculated, for every customer and prospect, it can be leveraged in the following ways:
With CLV, everyone in your company can agree on which products, customers, and prospects to focus on to improve corporate profitability.
B2B companies typically work with several Big Data sources – marketing automations, sales platform, billing system, and customer service to name a few. The sheer volume of data from these systems can be intimidating and taxing to an IT department. On top of that, business leaders are asking to have more and more new data sources (e.g., social media, natural language processing, operations performance) included in reporting and analysis.
This has precipitated in growing the popularity of creating a data lake for a company’s data. The data lake is basically one central location where data is placed from every system, platform, file, spreadsheet, audio file, and whatever else is deemed potentially valuable data. The good news is, all the data is in one place for people to access it. The bad news, it’s up to you to figure out which data to use, how to prepare it, and how to analyze it.
Don’t dive in headfirst.
There’s a lot of data in that lake. Make sure you are familiar with the different sources of data before you start using it – know the background on each source, which files can be joined to others, and how big the data is. Most importantly, have a clearly defined plan for how you are going to use the data in the lake and what business questions you want answered.
Use the buddy system.
If you are not an expert swimmer (in this case, a frequent user and analyzer of data), bring a buddy with you so you don’t get in over your head. Your buddy could be someone from IT, a Sales Ops reporting whiz, or someone from your analytics group. Bounce ideas off your buddy about the business questions you are trying to answer and how the data in the data lake can best be used.
Don’t go past the buoys.
Trying to do too much too soon may put you on a never-ending analysis path (and it will alienate your buddy). Start with some basic questions or challenges and use the data lake to address those. You will learn how to navigate the lake while also being viewed as a data-driven decision maker. Then move on to the more involved and challenging problems.
Know what’s in the water.
The data lake stores the data, but it doesn’t cleanse, transform, standardize, or join the data sources. It is up to you to learn what data you want to use. Have your buddy guide you to understand the data sources or direct you to the respective subject matter experts who know the details and pitfalls. You may find new data sources that you hadn’t considered and there may be data files that are too incomplete and inconsistent to even bother with.
Listen to the lifeguard.
Your IT director may not look the part, but he or she is the (figurative) person with the whistle telling you where you can swim and what the rules are. The data lake is not a complete free-for-all. There are data security rules, customer privacy considerations, storage space, and server access that IT still oversees. Follow the rules and stay on the good side of the lifeguard.
The only constant in customer loyalty is its variability. With more technologies flooding the market than ever before, brands have been forced into investment strategies that require patience, mobility, and vast amounts of research in order to find the tools and partners necessary to provide customers with an engagement experience that serves as a foundation for future loyalty.
In the pursuit of just how the market stands at this moment, we went straight to the source: the esteemed members of Loyalty360, the association for customer loyalty.
From customer data, to internal alignment, to the ever-present challenge of measurability, the questions presented to our members exemplify some of the largest issues, conundrums, and opportunities faced in the market today. Through the responses of thought leaders across a variety of technology and service suppliers in the customer loyalty and CX industries, we’ve created a comprehensive snapshot of the ecosystem as it stands today.
Brand sophistication ranges from very low or non existent, to very sophisticated when it comes to customer experience and loyalty. Some very large and well-known brands do not have a customer loyalty program that identifies high value versus low value customers. Historically their focus has been on broad based consumer marketing as opposed to developing information and programs for individual customers. These brands are having to shift dramatically due to the sophistication of their online-based competitors.
Our research shows that brands have made great strides over the past year delivering on customer’s expectations in terms of integrating new technology. Specifically, our 2017 Mobile Loyalty Report found that 64 percent of brands reported an increase in loyalty program membership over the last year, and the majority cited the addition of mobile components as the biggest contributor to this increase.
Rewards and incentives are a core part of most loyalty initiatives. For us, customer experience is also a priority when we develop our reward offerings, because that’s exactly what brands want for their target audiences.
Rewards and incentives should increase positive behaviors toward the brand and engagement and this means a user interface that equals a great experience. We’ve had great success integrating our technologies with the existing systems of our brand clients through our API, which allows clients to directly integrate and implement their application, loyalty platform, or procurement system without the disruption of existing system. This kind of seamless way to run loyalty programs is essential for brands to adequately track and implement initiatives along with all the other customer-facing outreach they are doing.
The best programs and customer experiences contain communications that have an aha moment. That moment is when a brand is connecting emotionally with a customer, when a message resonates so completely with the needs and desires of a customer. Technology is table stakes, and most brands struggle with integration, which holds them back from breakthrough marketing. Without a clear understanding of customers, their needs, habits, and lifestyles, brands are merely guessing. Humans are bad at guessing. Beyond technology, there is a need for guided analysis such as segmentation, predictive technologies. The ability to interpret data in a way that guides the organization is critical.
The biggest constraint, however, is knowing what to do next. Personalization can be successful based on purchase habits and preferences, life stage events, lifestyles, and inferred needs. However, this type of marketing succeeds with lots of small wins, not many home runs. The industry today is not as sophisticated as it will be in five years as technology, learning, and creativity evolve.
There are really varying degrees of sophistication when it comes to driving fully integrated experiences through the use of smart technology, personalized service, and relevant offers. At one end, there are brands that seek to be offer a full suite of products to keep pace with
marketplace expectations and generally encompass both offline and digital experiences. This me-too approach, while transactionally complete, may miss opportunities to provide seamless experiences, personalized offers, and relevant products. At the other end of the sophistication spectrum, you have brands striving to create holistic experiences across all channels, leveraging individual consumption patterns, real-time experience feedback, and intuition to propose offers that are highly relevant to the consumer.
In our experience, most brands are sensitive to the value personalized, highly relevant offers in their program but may have only partially optimized (against a channel or specific product). The short answer is that most brands currently operate somewhere along the spectrum between transactionally complete and fully optimized.
There are some excellent loyalty initiatives. However, most companies are still struggling to put all the pieces together. They may have excellent communications but might not be able to segment their database effectively so that each segment gets the appropriate messaging. They may have
excellent segmenting but not the ability to offer the kinds of awards that each segment finds motivating. They may have put an excellent program in place five years ago but haven’t assessed or made any changes since it was introduced.
Customers today want it all…a great customer experience and a targeted loyalty program that rewards them with outstanding awards and valuable offers.
Brand promises can be a bit misleading. It’s rare that a brand’s self-image matches up to the customer’s view of them. Brand promises often get hijacked to try and control the customer. You can’t control them, but you can understand them. Loyalty needs to focus heavily on their customer’s feedback, behavior, and transactions. That’s the first building block to great loyalty programs.
I can safely say from my experience that a brand should most definitely stay true to its own unique brand promise. More and more consumers are looking for products that align with their own values and sensibilities, as well as word- of-mouth recommendations, and they are not shopping by brand name alone. This makes it more vital than ever that brands are authentic and deliver on their own identity to make important connections with their target markets. From a reward delivery standpoint, a primary research study we did last fall showed that many brand attributes can be reinforced – or undermined, depending on the brand identity – simply by the way loyalty incentives are delivered and positioned. For example, personalization of rewards affected the individual’s perception of the brand – most said this approach made the brand seem smart, unique and caring. There is definitely a strong link between loyalty efforts and brand perception.
Brands that best meet the needs and desires of their chosen market will succeed. Those who know who their best customers are, what motivates them, and how their behavior is changing will continue to lead the pack. Having loyalty programs and other data capture mechanisms will help brands collect the data needed to define their market and core customer.
Brands should align with their customers first – always. They need to stay true to what the customer values them as. Not every customer wants their brand to be the next Apple. Brands need to stay current and relevant in terms of how the customer wants to interact and transact with them – but that doesn’t always mean the leading edge. We’ve seen many brands go down when they tried to change against their core values.
If you’ve worked, studied, talked about, or even taken a cursory glance at the marketing world in the last few years, you’ve no doubt encountered the words Big Data and the implications it brings. Brands are being flooded with data, and many are finding themselves unable to keep up with it using existing technology. The challenge, therefore, comes not in collecting more data but rather taking the data brands already have and making it easier to manage, analyze, and leverage to create actionable insight.
Data is complex, but we tend to think about data through the wrong lens. The issue isn’t reducing the data points, it’s that most loyalty providers look like a deer in headlights when it comes to analytics. Brands need to find loyalty partners, not providers. They need to find an agency that has resources devoted to finding actionable insights from their data. So, reducing data doesn’t really solve the issue. In fact, we need to dig deeper. Finding an experienced partner that knows how to cultivate data into insights and strategies is what can solve the data problem.
Brands today are collecting a plethora of data about their consumers from social, web interactions, purchases, and more, but this data often exists in siloes. Many brands lack a single view of the consumer, which denies them a deeper understanding of their customer and results in them missing the mark when trying to reach the right consumers at the right time. Getting a 360 view of your consumers doesn’t need to be a challenge. If you do not have a dedicated in-house resource, consider partnering with a loyalty solution provider and leveraging technology that allows you to capture data on your customers across all channels. Using this insight, you can group your customers into segments and leverage predictive analytics. From here you can create personalized outreach to engage customers in the right channel, with the right message, at the right time.
Marketers that are thinking about strategy, goal-setting, messaging, and personalization need to organize their thinking around the customer. In a strategic sense, brands must know the five or six types of behavioral customer segments they have and track if they are growing relationships through the lens of their customer segments. At a more tactical level, core behaviors, such as product category purchasing, frequency, channel, daypart, and marketing responsiveness can be used to customize and personalize communications. However, there needs to be common definitions and data consolidation to make this manageable.
– Cogensia Brad Rukstales President & CEO
It’s nearly impossible to talk personalization without acknowledging Jeff Bezos’s $500 billion elephant in the room, Amazon. The company’s success is owed in no small part to its ability to understand its customers and market directly to their personal tastes. The flipside of this impeccable customer experience is the shift it’s created in consumer expectations. Because so many shoppers have become accustomed to the personalized experience found at the e-tail behemoth, the bar has been raised for all other brands to a level that is often unattainable. Amazon has set the standard for customer personalization, and brands are scrambling to react in a way that both fulfills the demands created by the Amazon Effect, while also retaining a distinct company identity. Our members weighed in on the challenge and how a loyalty program can provide more personalized experiences.
Amazon is a great example of the power of personalization. I’m sure many people, like me, have found and purchased great products in the Recommended for You section. Many loyalty programs have a tremendous amount of data from which they could also build similar forms of personalization. I expect that we’ll continue seeing more and more companies delivering customized offers that tie directly to individual customer preferences and desires. What we’re excited about is how a loyalty program can leverage to go one step further. Not only can they understand consumer preferences and desires, they can also quantify the future stream of revenue from members that take the offer. If you could accurately estimate the future revenue stream of each member over some horizon, it opens the door for more opportunities to invest in that member because you have a clearer view of what the payback could look like. This means better deals for the members, more loyalty, and a larger bottom line for the business.
– Willis Towers Watson Len Llaguno Senior consultant
The biggest challenges for a full customer view continue to be identity management (tracking someone through all channels, digital and offline), analytics, and creativity. Personalization today must go beyond the standard personalization engines that recommend products based on similar baskets or collaborative filtering and more into the underlying preferences that customers display in their relationship overall. The opportunities are huge when personalization is done right. We see increases of over 50 percent in open rates and click through rates with personalization, and in some cases a 5x increase in store purchases.
– Cogensia Brad Rukstales President & CEO
In our primary research study, we did quite a bit of digging into consumer perceptions surrounding personalization. One of the things we found was that among women (who still make 80 percent of household purchase decisions), personalized incentives increase perceptions that a company is ambitious, cool, caring, and informative. While this is a great way to stand out and engage consumers, there are also challenges. In our study, a small percentage also said that personalization did not resonate with them, so it is vital for brand’s to truly understand their target audience and their threshold levels for personalization. For our clients, we’ve had great success with personalization techniques in engaging and communicating with their audiences, whether they be consumers, employees, or even survey respondents.
– Virtual Incentives Jonathan Price CEO
“Personalization today must go beyond the standard personalization engines that recommend products based on similar baskets or collaborative filtering and more into the underlying preferences that customers display in their relationship overall”
As artificial intelligence (AI) continues to seep into nearly every part of our lives, it’s time for marketers to step back and explore how the technology can be leveraged within the context of customer experience and loyalty. Because of the consumer’s (and consequently, the industry’s) increasing demand for immediate convenience, AI may be the perfect solution for marketers to stay in lockstep with customer preferences and, in some cases, even anticipate future behavior.
Machine learning, AI, and predictive modeling are great ways to synthesize data into understanding a future potential outcome. This can be a big benefit, especially for complex brands with lots of products and variations. Understanding who is likely to do what is an advantage when building promotions as well. As data sources continue to grow, and integration is well managed through platforms, the companies that utilize this technology will see benefits, since the ability to anticipate customers’ needs will be stronger.
– Cogensia Brad Rukstales President & CEO
I’m seeing a lot of brands leveraging machine learning. Machine learning is a class of algorithms that learns from data over time and can make increasingly accurate predictions about the data sets. This helps brands go beyond what is possible for humans to detect, and find patterns and insights that were previously unknown. Marketers are applying this tactic to loyalty program data in order to make relevant offers and targeted promotions. Brands are using machine learning to optimize customers’ shopping cart experiences based on previous behaviors, map customer journeys that predict new shopper behaviors, and create look-alike audiences that resemble their best customer segments. Machine learning should be an integral component of any customer loyalty strategy moving forward. These algorithms can help to enhance the customer experience and build engagement by delivering personalized content and product recommendations which helps to boost customer satisfaction and drive sales.
– CrowdTwist Emily Rudin Chief Customer Officer
As data capture continues to get better and faster, machine learning will give us the ability to see new correlations between groups of data sets that we never could before, unearthing patterns and increasing our understanding of behaviors for significantly better customer experiences. We’ll be able to create a kind of recommendation engine based on past behavior instead of using artificially created sets of rules to determine program content and offers.
– Stellar Loyalty Narina Sippy CMO
Implementing a new tool, cracking a tough problem, or finally hearing positive reviews on a new marketing campaign is always encouraging for brands, but the reality is that without measurement, these improvements are little more than aimless blips on the timeline. Measurability is the key to spotting trends and plotting a roadmap moving forward. Our experts are in agreement that without solving the challenge of measurability, loyalty efforts lack a sense of direction.
Accurately measuring lift from loyalty initiatives is very challenging because it requires the ability to measure an unobservable event. That is, it requires you to know what your members would have done in the absence of the loyalty program. If you know this, then you can compare it to what they actually did, and clearly see the impact. Of course, it’s impossible to observe this. Therefore, the best you can do is to create a proxy for the concept of lift. This is often done with some form of look-alike analysis or hold out/control testing. But this also has it challenges due to selection biases inherent in members that opt to join the program vs. those that don’t, even if by all other metrics they look similar. It’s even more challenging if you’re not able to track non-program members in a meaningful and consistent way. Many companies we spoke to at the Loyalty Expo were in this boat. Lift is absolutely an important metric to monitor, but given its challenges, it’s useful to have an additional financial metric available. Virtually all programs have enough data to build models to predict expected future revenue from individual members, say over a 24-month horizon. This can be a powerful metric to monitor, because when it’s increasing you know you’re increasing expected customer loyalty.
– Willis Towers Watson Len Llaguno Senior consultant
The biggest challenge our clients face is becoming the disruptor and not the disrupted in their industries. Customers want convenience and frictionless experiences, so brands need to look at the whole customer process and make it as simple and high-value for the customer as possible. This requires collecting and using data the right way and putting in place the right technology to keep your customer engagement programs relevant and nimble. At the end of the day, the customer experience is what drives measurable loyalty. If your customers are happy interacting with you, they will visit you more, spend more, and recommend you to others more. The ultimate measure of efficacy is revenue. If your program is not driving lasting revenue gains, then you need to take a hard look at where the ball is getting dropped along the customer experience line.
– Stellar Loyalty Narina Sippy CMO
After challenging our panel of members to discuss some of the trickiest topics in customer loyalty, our final question asked them to practice addition by subtraction: of all the opportunities for brands in the customer loyalty space, what is the single one you would recommend? The answers were interesting in that they illuminated not only the potential opportunities for brands but also which ones are being given top priority by technology suppliers.
Data shows that less than 30 percent of marketing budgets are allocated to customer retention. If we could recommend one thing to a client it would be to rethink this balance and be bold in investing in CRM, loyalty, and engagement marketing. The reality is that customers want to be loyal to their preferred brands but they often feel those same brands don’t know them or return their loyalty. Being bold means speed to action, testing, refining, and continually optimizing. Listen to your customers, identify opportunities to make an impression, then test and measure, refine and optimize. It might be as simple as providing digital coupons to shoppers for just the right products at just the right moments or sending an SMS text to remind a customer their favorite restaurant is just around the corner. You have to have the determination to do what’s right for your customer regardless of the way things have traditionally been done. Market evolution is happening at breakneck speed. The time is now to invest in your customers.
– Stellar Loyalty Narina Sippy CMO
In order to attract new customers and keep existing ones engaged, I’d advise brands to invest in a multichannel approach in your loyalty program. Keeping consumers loyal today requires more than just a simplistic spend and get program. Your customers want more. You need to be where your customers are, listen to what they have to say and become a part of the conversation. This strategy can help brands with the foundational work of integrating disparate data to form a holistic, data-centric view of their customers. From here you can drive better engagement by providing personalized customer experiences.
– CrowdTwist Emily Rudin Chief customer officer
The biggest challenge continues to be making sense of the data being captured and integrated. Experienced analysts know the right questions to ask and how to get the right answers to maximize marketing’s performance. Don’t skimp here. Some clients struggle with the organizational constraints on them in terms of ability to impact change. I believe that this will evolve over time, however.
– Cogensia Brad Rukstales President & CEO
Loyalty is in a state of evolution today, but it’s happening in fits and starts. Data is the driving force of most gains in the last five years and it continues to be that catalyst. Yet what many brands are realizing is most vendors aren’t set up to support those needs—it’s often “here’s a cool platform with lots of bells and whistles; be on your way.” Meanwhile brands are barebones on resources, they don’t have the bandwidth to cultivate data-driven strategies. So, the biggest opportunity is for brands to find better partners to help them evolve from last-generation programs and to match heightened customer expectations.
– Baesman Evan Magliocca Brand marketing manager
Businesses face many challenges today that impact traffic and same store sales. This includes pricing pressures, an aggressive competitive environment, a long- term decline in retail and slipping mall traffic, and an emerging generation of customers with different behavior than before. Amongst all of the challenges, businesses must have a deeper understanding of customers, their behaviors, demographics and attributes.
Marketing today must focus on current customers– who they are, how often they visit, and what they buy. In this environment, personalization is more important than ever. Businesses need to connect with their customers in a personal and relevant manner.
With the proliferation of data and online access, customers expect businesses to know them and everyone is fighting for their attention. Data is allowing many businesses to simplify, enhance and personalize the customer experience. Today, mobile apps track customers’ past and favorite orders for quick reorder and mobile pay makes it easy to get in and out of the store fast. POS systems show guest transaction history.
Websites make the right recommendations to customers. Some businesses are doing this well. However, many are not.
Our point of view is that businesses need to know their customers, show them that they know them and show them that they care. In an environment where customer loyalty can be fleeting, communicating relevant and personal information increases your bond with customers. Customer experience personalization is all about data first. Get the data right and you can shape the overall customer experience by applying data science and machine learning. Brands that personalize customer experiences by integrating advanced digital technologies and proprietary data are seeing revenues increase by 6 to 10 percent, which is 2 to 3 times faster than those that do not.
The following is our 4 step process to personalization for restaurant businesses that need to get on the journey of personalization.
Personalization starts with knowing who your customers are and what they deliver to your business. Integrate all your disparate customer data into a single place for analytics and action. Most businesses have many sources of customer data and it is often scattered throughout their organization; Certainly, point of sale transnational data that records all guest sales is highly valuable. In industries such as e-commerce and travel, the customer is identified. In restaurants and retail, this raw data is not connected to the customer. Other data sources such as online order information and guest e-club data and loyalty can be linked to transactions providing a starting point for knowing your customers.
Find Anonymous Customers
For businesses, there are external processes that can link a significant percentage of guests’ purchase data with point of sale data. This allows the companyto put a name and contact information to what would otherwise be unidentified purchase transactions. In many cases, this process can more than double the marketable customer base for a business.
Add intelligence to get 360 degree view of your customers
Start with a central repository of all guests data. Then append third party data to individual guests to get a view of not only their purchase behaviors but picture of who they are in life. Data appending allows businesses to fill in the gaps in customer data and add customer demographics (such as gender, age, income), lifestyle and interests (life driver segments, interests) and buying behaviors and attitudes (such as price sensitivity, technical aptitude).
Analyze and Summarize
With an organized and clean guest database, a business can now analyze and model guest data and determine the following:
Defining marketable segments and personas for a business is highly valuable for determining the business strategy and how to improve the guest experience, digital marketing, media buys and more.
Ongoing customer analytics keeps your guest data base up to date, migrating guests between segments as behaviors change over time. It is important to determine what is most relevant for guests on an ongoing basis
Following the customer analysis and summary of guest and business insights, identify the business opportunities. These may include:
Determine Your Strategy & Tactics
After you’ve defined some core opportunities, you can now determine your strategies and tactics to communicate with targeted guests. Determine relevant content and offers to guest segments and individuals based upon behaviors or demographics. Calculate the profitability of specific offers to understand the economic implications.
Drive Engagement with Relevant Offers
Knowing past behaviors and guest preferences, provide guests with meaningful and timely communications. For example, knowing your customers only shop at certain times of year and then offering products around that theme.
Integrate Your Plans
Integrate your customer communications with your overall plans to drive more business from customers in a manner that is relevant to them. Build out your calendar knowing your relevant holidays and high traffic periods. Leverage your vendors and to delight the customer.
This is where the art and science of marketing meet.
CRM Tools enable easy and automated execution of your strategy. A Customer Management Platform (CMP) gives businesses easy access to query and select current customers by all their data dimensions: location, defined segment, product purchases, frequency, value and demographics. Marketing campaign lists can then be selected from the CMP for automated or ad hoc campaigns.
Set up Campaigns to Test List, Offers, Creative and Communication Channels.
Select customers and test various offers, creative and communications cadence. Dynamically personalize creative and deliver messages through channels that are most relevant to each guest. For example, an afternoon guest can receive a relevant email and mobile app messaging communication mid afternoon on a weekday versus a low tech guest receiving a direct mail postcard with a new special. Personalize your website experience based upon guest profile and behaviors. Reach guests in the channels where they are including mobile and social. In all cases, a clear message and a single call to action drives response.
Just to note, we are finding that direct mail is not a dead channel as some proclaim. While millennials are digital natives, 92% of them are influenced to make a purchase decision by direct mail as opposed to 78% of email.* Per the DMA 2015 report, direct mail response outperforms all other channels by 600%. Integrate online and offline communications. The goal is to engage customers to drive business and get a positive return on your marketing investment. Strategically invest more in high potential guests with an integrated campaign to drive greater business. DM costs are high but in the end it’s all about your ROI. You may spend more to get more.
Automate & Personalize Trigger Campaigns
Set up automated communications based upon lifestage or behaviors to drive customer engagement. These may include lapsed customer communications, daypart drivers, e-Club welcome communications, birthday offer, purchase thank you note and more. Add intelligence to these communications and personalize. Set them up once and automate this execution. Test and refresh campaigns as results are measurable.
Adhoc Marketing Opportunities
Launching new items will interest select customers. Market changes and promotions to targeted customers to drive repeat traffic with relevant communications. Respond to competitive actions or poor store performance with direct customer marketing to targeted guests in specific geographic areas.
Leverage your guest data and CRM tools to strategically invest in your guests with the right tools and dynamic execution.
While many marketing campaigns can be arranged as “set it and forget it”, it is important to continuously measure the impact of your marketing. For email, results are more than open and click through rates, but should look at customer offer redemption and purchases. As your CMP is updated regularly with your customer purchase data, track your customer coupon redemption and purchases by campaign. Effectively closes the loop on your marketing with purchase results to determine your most effective marketing campaigns and ROI.
Continual testing provides learning. For example, as a company is launched its campaign, they divided the campaign into three distinct groups based upon past behaviors. The targeted emails had 2x open rates and 5x purchase rates! Getting relevant with customers drives results.
The proof is in the results. Personalization gets the guest’s attention and drives engagement and sales.
Now is the time to drive more business through personalization. Know your customers, show them that you know them, and show them at you care. See what we can do for you.
Shortening the sales cycle, increasing order size, and bettering company practices can be daunting tasks. All of this could be managed with ease though if B2B companies harnessed and broke down Big Data. These five steps will help you get the most out of your data.
To start off, you must understand which data sources you are currently using to target and inform sales and marketing efforts. Most companies have a marketing automation platform, sales platform, CRM system, and firmographic data for their customers and prospects.
Identify data that you could use for targeting your sales and marketing efforts. Check with IT, sales, and marketing to develop the full inventory of data that is captured and stored. Sometimes you’ll find a valuable data source isn’t being used simply because nobody has asked for it.
Allow your imagination to run wild and create a data wish list to help meet all your objectives. This may consist of data that is hard to capture and digitize, third-party sources, or primary research. Everything comes with costs and challenges (otherwise it’d have already be done) but you should always know what options are out there and their cost/benefit analysis.
Once all the data sources have been evaluated and collected, you’ll need to make it real by creating a vision and action plan. How will this Big Data deliver more relevant marketing and advertising? Will your sales representatives have more insightful conversations? Decide upon this and show senior leadership that the benefit will outweigh the cost by improving practices, enabling new strategies, and delivering a strong ROI.
This is the most crucial yet difficult step. To effectively use Big Data, you’ll need to steam multiple data sources into one customer/prospect view. This involves navigating corporate politics (and data fiefdoms), making your case, and having a way to leverage the data to sell more effectively.
Leveraging Big Data is not easy, but if done effectively it can be a competitive advantage and help you meet and exceed your business objectives.