Financial Advisor: Prospecting Ideas Using Data Modeling

financial advisor prospecting ideas

If you are a financial advisor or a wealth manager, then you know that the financial services landscape is highly dynamic. Financial services trends and regulations change frequently.  Marketing in financial services generally has a long conversion process due to the sensitive nature of the information that clients have to share with their wealth managers. Financial advisor prospecting ideas and activities, therefore, have to constantly be refreshed.

Data-Driven Prospecting Ideas for Financial Advisors & Wealth Managers

Think about how you typically market a financial services company. Prospecting ideas for financial advisors generally means cold calling or relying on referrals. These approaches are not without their challenges or issues. Referrals, of course, can be an effective way to find new clients. However, even your referral strategy can become more precise when driven by data.

In fact, it can be even more beneficial to begin with data. You may already have plenty of it. But, it may be fragmented and uninsightful in its present state.

Wealth Profiles

Your data needs to be housed in a centralized database, collected and organized into wealth profiles. Even if you are an individual financial advisor or wealth manager, organizing your data can be the first step in gaining actionable insights.

prospecting ideas for financial advisors

Wealth Indicators

Take wealth indicators for example. They can be a great starting point in understanding where the greatest potential lies in your database. Furthermore, you can combine wealth indicators with demographic, lifestyle, interest, and affinity data. Doing this gives you a holistic picture of who your contacts are.

For instance, you may find two contacts who are both 55 and have a net worth of $8M. When you perform a wealth screening, you might see that prospect A is interested in golf, whereas prospect B is interested in opera. Imagine you now approach them with a richer image of who they are. You will be more likely to have an engaging conversation with them.

Other data-driven,  prospecting activities for financial services involve deeper analysis. Analysis and modeling can further elevate your prospecting ideas. Let’s explore how.

Data & Modeling: Using Deeper Analysis to Drive Prospecting Activities for Financial Advisors

Leverage Your Current Customers

 1. A Look-Alike Model

You can leverage your existing contacts through modeling. A look-alike model can analyze your best customers and look for patterns among them. These patterns can then drive your prospecting activities.

For example, the model may tell you that all your top clients have a net worth between $1-3M. That a large majority of them do not have children and that they prefer adventure travel. Geared with this persona of an ideal customer,  you can tailor your prospecting ideas to really speak to someone like this.

2. Inner Circle

Although this technically is not a model, WealthEngine’s inner circle feature can make a big difference to your referral marketing. Basing your financial services prospecting on data from this feature can give you a sharper focus. Your current customers can again be a great source for you to meet great new customers. A warm introduction from your client to his colleague or HNW friend can automatically generate trust.

Let Your Prospecting Ideas Get Predictive With Modeling

You can use wealth models to predict specific outcomes. Predictive models build a specific formula for your client base. The model then uses this formula to analyze your database. Everyone on it will be scored against the formula and divided into segments. These segments will, therefore, help you prioritize your prospecting activities. A formulaic analysis, like this, can help you with the following:

1.  Customer Acquisition

This model can help you identify a completely new customer group. The group will be a high-potential segment as it will have properties that are similar to your existing customers.

2. Conversion

In this case, you can identify customers who were successfully converted to higher spending. We will build a model that can understand these customers. The model can then pick out other customers who can be upgraded.

3. Upsell

The upsell model builds a formula to predict upgrades or complimentary services. Through this, you can identify customers who can be approached with other offers.

4. Retention

For any financial advisor or wealth manager, customer churn can be a major concern. Using the retention model helps you predict whether a customer will churn or not.

5. Customer Lifetime Value (LTV)

This model can predict the lifetime value of your customers. This way, you can focus your attention on those relationships that have long-term potential. How does this work?

The model uses your customers’ transaction history. Doing this enables it to predict churn. Further, you can also forecast the number of future transactions, the value of future transactions and even the next transaction amount. This type of analysis is possible using the latest machine learning techniques.

Therefore, data-driven, financial advisor prospecting ideas lead to more efficient prospecting activities.

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Understanding WE Analyze to Learn What Makes Your Prospects Tick

Understanding WE Analyze

WE Analyze allows you to harness the power of WealthEngine’s data and modeling capabilities to transform your decision making. This tool helps you gain insight into your audiences and find prospects just like your best customers and donors. But, how does it work? What does it provide? And how can you use it to create a loyal base? Let’s dig into the details so you can gain a better understanding of WE Analyze.

Understanding WE Analyze: The Ins and Outs

Before using the tool, it’s important to gain an understanding of WE Analyze. The WE Analyze tool allows you to create a ‘look-alike’ model so you can find your best prospects. Essentially, WE Analyze helps you identify elements of your past successes and helps you replicate the process. So, instead of sending generalized email or direct mail campaigns to prospects you can gauge their interest to see what resonates with them. You can use the solution to find people with the same characteristics as your best donors or customers. When you talk to people who are similar to those who have responded before, your conversion rate increases.

Find your next best prospect today. Follow these three steps to make the best of WE Analyze:

1. Upload a list of your best customers or donors

When uploading a list, all you need to do is load a list of names of your best customers and donors, along with their corresponding address or email.

2. Generate a ‘look-alike’ model

Once you’ve logged in the names you’d like compiled in your list, WE Analyze then maps your list utilizing thousands of attributes on nearly every adult in the US. This provides you with a holistic view that includes insights on demographics, lifestyle, wealth, and more.

3. Use the model to personalize your outreach

Now that you have your model, you have a better understanding of how to interact with your top prospects. What does your audience care about? What motivates them to act? This lays the foundation for you to personalize your outreach and appeal to donors and customers in ways that are more aligned with their needs.

Using WE Analyze, not only are you given the insights on which prospects will convert, but it also gives you insights on why they will convert. Let’s take a look at some of the features to keep your eyes on as you navigate the tool.

Understanding WE Analyze Through Helpful Dashboards

Another key step in understanding WE Analyze is grasping the function behind the unique dashboards. In the Analyze tool, there are dashboards to help you learn more about specific groups of individuals from your list. These dashboards help inform your strategy, decision making, and event planning. So, you may be wondering: what are some of the dashboards in the tool? Let’s explore the various dashboards you can use:

Wealth Dashboards

The wealth dashboard contains a collection of charts that break down your lists of customers by net worth, investable assets, types of investors, and more.

Based on the information gathered here, you gain a greater sense of what’s most appealing to different people.  This helps you assess what, in your particular set of offerings, will appeal most to specific groups. So, it’s important to ask yourself: What type of products, investments, and services do we offer that’ll be most appealing to this, specific group? Would they respond well to a mass email campaign or a direct mail campaign?

Giving Dashboards

The giving dashboard is geared toward nonprofit organizations. This dashboard breaks down Propensity to Give (P2G) scores, giving capacity scores, and visual overviews. P2G scores (measured on a scale of 1 to 5 (1 representing the highest ability or propensity to give), allow you to understand the giving behaviors of existing and prospective donors. This will help you develop a strategy to appeal to top donors.

Therefore, the information provided in this dashboard enables you to create realistic fundraising plans for your next campaign.

Demographic Dashboards

The demographic dashboard provides an overview of the genders, age ranges, education levels, and geographic location of your existing database. So, the information compiled in this dashboard informs annual fund appeals. It also informs marketing campaigns because you gain a greater understanding of the groups you’re appealing to.

Modeling Scores: What They Measure and How They’re Used

The last step in understanding WE Analyze? Creating models of your best donors and customers, so you can find prospects just like your top contacts. After you’ve analyzed your list, you can now prioritize identifying the overlapping characteristics and qualities among them. This method of modeling can help you identify what qualities your ideal prospects would have. Those people, who look similar to your loyal consumers, are your best prospects. So, how can you measure which new prospects are a “good” match? In other words: what is a “good” model score?

Model scores exist on a scale of 1 to 100 (1 being the least similar, and 100 being the most similar).  In general, scores at 60 or above are ideal. These scores indicate that the prospects you’re looking have the most similarities to your existing donors or customers. For example, if 10% of people scored 80 or above in your model, this shows that this group of people are just as likely as your existing clients to give or spend.

Furthermore, model scores between 50 and 59 are considered decent, where prospects hold some similarities with individuals you’re modeling after. But, the lower the score, the less likely those prospects are to resemble people you’ve modeled after.

Customers Who Have Benefitted From Understanding WE Analyze

One of WealthEngine’s clients, The Humane Society (the largest animal welfare organization in the US), wanted to identify more supporters for their cause. They wanted to not only bring in more donors but also deepen donor involvement.

Using WE Analyze, The Humane Society was able to create models for the major gifts program and their mid-level program. By doing this, they were able to identify valuable prospects to connect with, as well as segment and optimize their fundraising practices. Additionally, after using the tool, they saw a 20% increase in mid-level appeal programs.

Understand and Make the Most of WE Analyze On the New WealthEngine9 Platform

WealthEngine9 or WE9, our newest release, is transforming the nonprofit and commercial prospecting landscape. Explore how our Engagement Science™ speeds up the way you screen, analyze, find insights, and predict outcomes through modeling.

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Donor Segmentation: How Models Can Drive Personalized Campaigns

customer segmentation models

Fundraising success comes down to well-timed and optimized asks. Donor segmentation can help you find the best prospects for your campaigns. Yet, segmentation is not an end in itself. Its impact grows when combined with donor segmentation models. These models can also increase personalization and engagement.

What is Donor Segmentation and How to Segment Donors

Donor Segmentation is the process of breaking donors into categories. For example, you can categorize them by their ability to give. Donor segmentation fundraising is different for every organization. To illustrate, a nonprofit could segment donors based on past giving. Yet another could choose to segment by wealth brackets.

Donor Segmentation Analysis

Segmentation analysis helps you find macro patterns in your database. This can help you understand what makes your donor base unique.  At this level, you can form macro segments based on geography, age-range, wealth score, and P2G.

For instance, your donor segmentation analysis could reveal that 60% of your donor base is over the age of 50. Your donors may have worked at large corporations. Over 45% may have an interest in local sports.

These details are crucial for you to see what makes your donor base unique. When you zoom in further, you may see that over 70% of people with these traits are regular donors. This then becomes an important segment for your advancement team to focus on.

WE Analyze can create such a model from your data. This donor look-alike model allows you to apply these patterns to your database. Doing this allows you to find more prospects who look like your chosen segment. Thus, donor segmentation analysis can also help to drive predictive prospecting. This includes finding look-alike prospects that match the profile of your best donors.

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Success from Look-Alike Model

For instance, Multiple Myeloma Research Foundation (MMRF) wanted to identify potential high-impact donors among a large prospect list and prioritize outreach to those constituents. WealthEngine created a donor look-alike model based on their best donors and then scored their existing prospect list using the model.

As a result, MMRF was able to connect with more high-impact donors in just two months.  In this period, they were able to gain 3x ROI on their campaign efforts.

Pleased with the results, Michael Hund, Director of Development has said:

“This is a revolutionary product that every single nonprofit should be using.”

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How You Can Increase Campaign Precision Through Models

You can categorize your macro segments further to refine your strategy. Custom models increase precision and enable you to predict giving.

Modeling goes beyond finding look-alikes. It can actually help you predict giving. For instance, WealthEngine’s custom models can forecast major gifts.

Donor Segmentation Models are not restricted to current members of your nonprofit. In fact, models can enhance fundraising at every stage in the donor lifecycle.

Segmenting your donor base based on lifecycle stage offers many advantages. You can identify current donors with major potential. Plus, you can win back former donors and prevent churn.

You can also use donor segmentation models to optimize your ask. This is especially important when it comes to donors who have high P2G scores. Optimizing your ask means that money hasn’t been left on the table that could have gone towards your cause.

Refined Donor Segmentation Also Enables Personalization

Furthermore, refined donor segmentation enabled through modeling helps you fine-tune your messaging. A personalized message that reflects customer interests is more likely to resonate.

Take your ideal donor segment for instance. You can divide them into smaller groups based on the type of sport that they follow. This enables you to not only tailor messages you send them but also create valuable experiences that match their interests.

Personalization (leads to)–> Message Resonance (which increases)–> Donor Engagement (Which results in)–>Better Lifetime Value.

This means that your donor remains connected to your organization and cause.  Moreover, LTV is a great metric for you to prioritize your prospects on. Prioritization means your budget and message focus on the most responsive segments. Thus, your efforts will see increased conversion at reduced costs.

Machine Learning Enhances Donor Segmentation Models

The more you use donor segmentation models, the better it is for conversion. WealthEngine’s machine learning capabilities ensure that our solution’s predictive algorithm is always improving. When you refresh your model every 15-18 months, you will have the most up to date prospect list for any campaign.

Increased precision leads to increased engagement. Moreover, increased engagement results in higher conversions and lower costs.

customer segmentation analysis

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Learn more about how WealthEngine’s data science team can help. Gain deep insights to increase conversion rates through donor segmentation models.

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University Fundraising: Use Modeling to Identify Overlooked Prospects

university fundraising

Did you know that your screening data can help you find overlooked donors? Wealth Screening is not a new concept in university fundraising. WealthEngine’s solution WE Screen has helped several higher education institutions understand their alumni base by appending a breadth of data. For instance, Northwestern University used WE Screen to enhance their development efforts.

Prior to the first parent screening, their Parents’ Fund raised approximately $500,000 annually. Within the first year of screening, they found that the Fund had doubled. Within four years, the Fund had almost quadrupled to $1.75M.

Screening is a great start. However, higher education fundraising has a little known secret that few educational institutions use. The secret is modeling. When you create a model of your past donors, you learn unique insights about your contacts. Continue reading “University Fundraising: Use Modeling to Identify Overlooked Prospects”

Major Gift Fundraising: How Top Fundraisers Forecast Fundraising Income

major gift fundraising

Forecasting fundraising income accurately is important in hitting your major gift fundraising goals. WealthEngine’s Senior Client Engagement Manager, Eric White, shares how top fundraisers use data modeling to predict major gifts with extraordinary accuracy, including predicting donor likelihood, the right “ask” amount, and donor lifetime value.

Analyzing Your Screening Data to Understand Major Gift Donors

Major Gifts Officers often feel pressure to convert prospects to donors within short lead times. Yet, most development teams know that lead time can sometimes be as long as 24-36 months.

Major gift fundraising is about the quality of prospects and not the quantity. Fundraisers need reliable prospect research to develop a reliable, high-quality prospect list. It is in fact data that makes prospect research more reliable.

WealthEngine’s WE Analyze solution enables you to understand what makes your audience unique. Moreover, analyzing your screening data through WE Analyze provides you a 360-degree view of your donor base.

WE Analyze can create a descriptive look-alike profile. Knowing what makes your audience unique through this profile helps you make your communications more engaging.

For instance, let’s say your nonprofit is hosting an event in LA with 500 confirmed attendees. Running the RSVP list through WE Analyze can reveal that 70% of them are married. Further, it can reveal that 13% love antiques and 45% support children’s causes. This empowers you to tailor your major gift fundraising strategy. You can now approach the right major gift donors with relevant contexts.

In one such example, a WealthEngine client was looking for a sponsor for their fundraising event. Through WE Analyze, they realized that a majority of their attendees owned Mercedes Benz cars. They were also in the market for a new car. This created a great opportunity for them to approach BMW for sponsorship. For BMW, it was an opportunity to reach people who were primed for purchase.

Data Modeling for Predictive Major Gift Fundraising

When it comes to major gift fundraising, you can go beyond descriptive models into actual predictive models. Predictive prospecting can be a data-driven way for you to ensure that you target the right prospects.

Modeling uses statistical analysis that relies on a custom formula. The formula is specific to your organization and helps answer a specific question. Wealth models are predictive because they are built on strong indicators of major gift giving. Examples of indicators are the number of events attended, gift capacity, the existence of a family foundation, etc.

Indicators vary by organization. For instance, let’s say your organization has found that a majority of major gift donors are all concentrated in California. You could also find that they are all pet owners and have college degrees. These would all be categorical data points that come from your database. These categorical points can be given a numerical value.

university fundraising

Therefore, the model would consider this information and build a formula specifically for your organization. Further, it can specifically focus on your nonprofit’s major gifts fundraising.

In the instance above, zip codes in California, college degrees and pet ownership will all bear greater impact in the formula. The formula then generates a score by calculating the weight of all these characteristics. This means that you can now score your entire donor base against the formula. Anyone with a high score is a top prospect.

Automating Your Major Gifts Forecast

The model will actually score your entire database for you. Further, it will divide your database into 10 equal deciles. This means that you can already see who your top 10% of prospects are. Decile 1 represents your top 10% of prospects, deciles 1 and 2, your top 20% and so on.

wealth modeling

Now your major gifts fundraising has been prioritized for you. The probabilistic indicator within the model tells you who is most likely to donate. This is not just indicative of major gift giving. It is indicative of major gift giving to your nonprofit.

In one instance, a WealthEngine client saw that their capital campaign had stalled. The organization, a higher ed institution decided to use modeling to boost its major gift fundraising. Their custom model divided their database into 10 deciles in order of likelihood of giving. Their major gifts officer then decided to optimize their portfolio with prospects taken directly from the model.

After the campaign, the major gifts officer called us to let us know that they saw an 86% conversion rate by using the model. This means that 86% of the prospects addressed by the campaign said yes to giving.

You can automate major gift fundraising further through the use of API. Through API integration, you can score everyone that walks through the door. This can happen in real-time. Any new prospects can be scored against your major gift model and you can immediately receive an alert.

WE API

Reducing Lead Times Through Donor Models

Data models for major gift fundraising automate prospect research. Additionally, they go a step further and prioritize your prospects in order of likelihood. You may already be using WealthEngine’s Propensity to Give (P2G) score to prioritize and segment your donor base. It is important to note that the P2G score is a strong indicator of giving. However, it is not an indicator of giving to your nonprofit specifically.

The model generates results and organizes your donor base in a way that focuses on top prospects for you specifically. For instance, Bill Gates is an obvious P2G 1 donor. This doesn’t mean that he is likely to give to every cause. The model may identify somebody with a P2G 2 or 3, but the difference is that they are likely to give a major gift to your cause. This is because the formula in the model was built specifically for you.

When you focus your major gifts fundraising on such a targeted set of prospects, lead time can be reduced significantly. In one instance, a WealthEngine client was able to start having meaningful conversations with 20% of their top prospects about gifts in the $100,000 range. The remarkable thing about this story is that it only took them two months to identify these top prospects.

Another interesting point about this story is that all prospects identified in their top segment were ones who had never given to the organization before. This means that their top segment had been overlooked by the nonprofit before modeling.

Forecasting Fundraising Income

As we’ve established, WealthEngine’s data model automatically identifies your best prospects. Further, it prioritizes them in order of major gift capacity and propensity. This means that you can assign prospects within these deciles to your major gift officers. Knowing their lifestyle, interests, and affinities also helps officers approach them with relevant messaging. Gift capacity ratings and wealth scores give you an idea of the appropriate ‘ask’ for each prospect.

You can use let’s say the top 3 deciles or the top 30% of your donor base for your major gift fundraising. This means for the next 12 months, your officers will know who to target. Since deciles are organized based on strong indicators of giving, you can also predict giving amounts based on the number of prospects targeted at each gift capacity bracket.

Eric confirms that the data in a model can stay relevant for as long as 12 months. After this, you should run a fresh model to get the most up to date information for your major gift officers. Since prospect life stages are changing- inheritance, stock value, real estate ownership can all change over the course of 12 months. Refreshing your model to see what formula is most effective for your organization will help set you up for your next 12-month period.

Learn More

See how a data model can help forecast your next 12 months of major gift fundraising. Model your data now.

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Increase Grateful Patient Giving by Modeling Your Nightly Screenings

grateful patient program

Grateful patient giving has a little known secret that few healthcare organizations use: modeling. When you create a model of your past donors, you learn unique insights about the donor profile of your ideal grateful patient candidates.

You can then use your customized grateful patient giving model to score all future nightly screenings in a way that narrows your list of qualified prospects to the most likely donor candidates. This makes your grateful patient fundraising effort much more efficient while saving your team time and generating more revenue faster.

Grateful Patient Giving

Grateful patient giving has enabled health systems to raise $10 Billion according to the Journal of American Medicine. When a patient receives treatment and expresses immense gratitude, they may be a candidate for grateful patient fundraising. Past patients or patient families have a natural affinity for your hospital and are usually good prospects.

Your health system may have set up a nightly screening routine as part of your grateful patient fundraising program. Nightly screenings ensure that you continue to identify prospects when new patients come in.

These screenings also help keep your database up to date as customer net worth and lifestyle attributes change over time.

Grateful Patient Fundraising Using Screening

Regular screenings can serve as the foundation for your Grateful Patient Program. Nightly wealth screenings help ensure that you don’t miss any opportunities. They enable you to see a complete picture of a patient’s wealth, lifestyle and affinities.

For instance, WE Screen merges our proprietary wealth scores and ratings with your contact data. Now you know what we know about your contacts’ wealth, income, lifestyle, and affinity.

When you review and track data from your screenings regularly, you can act on it right away. For example, let’s say you had 10 new patients check in on a night. By the next day, you will already know which one of them is a candidate for grateful patient giving. You can ensure that you start to nurture the relationship right away.

One of our clients, a large American health system went from raising $19 million to $47 million in one fiscal year.

In fact, the VP of Philanthropy Services at this organization said, “…when a physician is referring a patient to us we can quickly get back to that physician to say that particular patient, that prospect now might have some capacity. Let’s figure out how to engage that person. With WealthEngine, with the ability of the gift officer to go directly to the website and receive these reports it reduces the time and it’s much more actionable for that gift officer in real time instead of waiting for the administrative staff to provide that report to them.”

A Grateful Patient Model Reveals Much More

Grateful patient screening is only the tip of the iceberg when it comes to grateful patient giving. Subsequently, you can extract actionable insights from your screening data. What if you could find prospects that look like your best donors? You can accomplish this by learning from past successes in your grateful patient program.

Our client, a healthcare foundation has said, “We see the value of maximizing the screening data to help us focus on building the right relationships and make targeted asks throughout the year. We have created a development strategy to make that happen and are eager to get started.”

For instance, you can upload your data from screening directly into WE Analyze. The solution finds patterns of traits among your patients.  These are traits that your top donors have in common.

For example, you could find that most grateful patient fundraising has come from patients who live in a 50-mile radius of the hospital. Further,  donations could have come from parents of young patients. These patterns can then be fed into a data model.

The model will divide your database into segments based on the likelihood of grateful patient giving.

Use Insights from Your Models to Predict Giving

Patterns that are fed into the model can help you find more prospects like your top donors. This means you now have a data-driven way to predict grateful patient fundraising.

With over 20 analytical models, WealthEngine can model your grateful patient screening data to identify the best prospects for major gifts, annual gifts, planned giving and much more. Models can also help you craft a capital campaign to raise money for a new wing, building or program. Models that use machine learning and artificial intelligence, like the ones WealthEngine creates, take the guesswork out of finding more grateful patients, retaining existing donors and growing their commitment.

Another WealthEngine client, a health system based in North Carolina used their screening data to create a model for their major annual fundraising event. As a result, event proceeds went from $400,000 to $7.4 million. A grateful patient model can make your efforts more targeted and increase donor lifetime value.

WE Insights: Get a Free Sample of a Model of Your Data

WealthEngine has a free service for clients in which they can get a sample model on actual data. Here’s an example of some of the insights you can learn:

average donor profile

More so, you can use your model to personalize your message to your prospective donors. WealthEngine’s models reveal detailed information about your past donors so you can see how well new prospects fit with the profile of past donors.

major gift donor profile

Contact WealthEngine about WE Insights to see a profile of your nightly screening files.

Score New Contacts with Your Model Using an API for Instant Results

Screening is the first step of your Grateful Patient Program. Analyzing and modeling your screening data allows you to prospect with high predictability.

Predictive prospecting creates a profile from your existing patients’ demographic, lifestyle and interest related attributes. This information generated by a predictive model, helps you identify your next best prospects. Predictive prospecting allows you to have a more targeted approach. This means that you reduce conversion costs while increasing efficiency.

You can increase the efficiency of grateful patient fundraising through API implementation. WealthEngine’s API can seamlessly integrate into your existing CRM and provide you updates in real-time.

Our client, a $6 Billion health system has said, “We built an integration with WealthEngine’s API. We have really got an automated process where our daily census can be screened, can be both matched and screened virtually automatically with very little intervention from us.”

Learn How to Model Your Screening Data

Learn more about how your nightly screening data could help you increase conversions and lower costs. Model your data now.

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Healthcare Fundraising: Boost Grateful Patient Programs with the P2G Score

How to Create a Wealth Model of Your Best Prospects

wealth models

When it comes to fundraising and marketing, acquisition costs can be measured not only in dollar value but also in time. It is important to spend time and dollars on the right kind of prospects. Wealth models can guide fundraisers and marketers to focus their time and efforts.

What is a wealth model?

A wealth model is a statistical model or an algorithm. It is based on a mathematical formula. Data scientists create these formulas to identify common traits among your customers, donors, and prospects. They have the capability to even convert certain qualitative attributes into quantitative scores.

Instinct usually determines the most predictive characteristics of top prospects. Wealth models help validate your instincts by quantifying and measuring data. This means that as a fundraiser or marketer your educated guesses can now be data-driven decisions.

How does wealth modeling work?

The idea is simple. A wealth model helps you answer a specific question. Wealth modeling is like perfecting a recipe. Data scientists take different ingredients in exact proportions to create the perfect model. Correlations between data points help you find your next best prospects. These correlations are much more reliable than any one single attribute.

For instance, let’s look at building a major gifts model for a university. The model must answer a specific question. Let’s say that the query is to find donors with a gift capacity of over $25,000 out of a list of 100,000 people. The wealth model first considers past behavior. Everyone that has made a contribution of $25,000 or higher will be included in the results.

wealth modeling

WealthEngine’s models establish a sample size of 200 or more. This means the machine learning in the model will look for donors with high gift capacity. It also means that the algorithm will go a step further to redefine the gift capacity or metric until a reliable sample size is established.

In the previous instance, if there are over 200 people that have donated over $50,000 the model can recommend this as a benchmark. Conversely, if it is only possible to find over 200 people who have donated $22,000 and more then the model can reset the benchmark accordingly.

How to use a Wealth Model

The quality of data determines the strength of wealth modeling. Therefore, modeling with reliable data gets you closer to your next best prospects. Wealth models can help segment your database based on capacity and propensity.

Raw scores generated by the algorithm help rank prospects. You can then start to segment top prospects. Refined segmentation helps you personalize offers and nurture prospects.

The benefit for marketers and fundraisers here is that the model brings you to the right neighborhood of prospects. You can prospect with confidence as your decisions are backed by data. The wealth model helps keep the right people and removes ones don’t meet your goal.

You can also customize wealth modeling to your industry and organization. Instead of looking at benchmarks that may not apply to you, you can focus on attributes that truly affect your business.

For instance, if two competing luxury goods companies run wealth models they might find different patterns within the same database. Company A might find that the correlation between zip code and number of cars owned is important. Whereas, company B might find the correlation between age and interest in travel are most important for them.

In this case, companies A and B would not benefit from a generic model for luxury goods companies.

Additionally, wealth modeling can also help you calculate donor lifetime value. This can act as an indicator of major gifts and recurring donations. It can also reduce donor churn and acquisition costs.

How WealthEngine Builds Wealth Models

What makes WealthEngine’s analytics unique is that we build custom models for your industry and organization. This means they truly reflect patterns in data that are relevant for you.

WealthEngine’s wealth modeling goes beyond the industry standard of analyzing 70% of any data set.  In fact, we use 90% of your data file and use the rest of the 10% to validate the file up to 10 times.

Our models generate raw scores to help you prioritize. Further, they create 10 deciles so that data is pre-segmented to show you the top 10% of prospects. You could then choose to target the top 20%, 30% and so on.

Our process uses standard econometrics and tree-based modeling to show you where your top prospects are clustered in a continuum.

Enterprise models give you unlimited opportunities to answer fundraising or marketing questions. You can input every attribute in your database into different wealth models. Each model addresses a specific need. These are custom built for your organization so they highlight patterns that are most relevant to you.

Custom models give you the option to input 6 key attributes into our analytics solution. This is an affordable way to generate more controlled models that are still specific to your organization.

Both types of models are capable of accepting numeric and categorical variables.

Learn more

Find out which model delivers the best results for your organization. Get insights now.

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Empower Prospect Research with Artificial Intelligence & Machine Learning

artificial intelligence & machine learning

The applicability of Artificial Intelligence & Machine Learning has been growing in every sector. In fact Forbes predicts that, “AI and machine learning will no longer be considered a specialty and will permeate business on a deeper level.”

At WealthEngine, Artificial Intelligence and Machine Learning are terms that are part of our Zeitgeist. We deal with these technologies every day when it comes to platform optimization. In fact, our new release WealthEngine 9.0 is all about automation and continuous learning.

This means you get accurate and up-to-date data to fuel personalized, wealth-aware campaigns.

Artificial Intelligence, Machine Learning, and Prospect Research

Artificial Intelligence helps analyze your database and build predictive models. You can use these models to identify your next best prospects. Further, Machine Learning automates the learning process to give you refined, personalized insights. In effect, the more you use the platform, the better it gets at serving your needs.

For instance, you could give us a list of 100,000 people with over 100 attributes for each record. This seems like a lot of data, but the Artificial Intelligence that powers the engine quickly analyzes these records. The engine recognizes patterns among top donors. These patterns are different for every organization. Therefore, your custom model helps you find new prospects like your top donors.

Machine Learning continuously refines your model. You can find top prospects in your database and convert them. While you do this, the algorithm sharpens itself to make the process faster and more targeted.

How do Artificial Intelligence and Machine Learning empower your organization?

The idea is simple. Models built specifically for your organization result in increased fundraising and marketing efficiency. Our predictive score is a strong indicator of conversion. It helps lower acquisition costs by enabling you to focus on top prospects.

When causes and corporations become efficient, they level-up entire communities! McKinsey reports that Artificial Intelligence is seeing niche applications in several social sectors. Plus, the technology has great potential to be scaled up.

Besides Artificial Intelligence and Machine Learning, we have defined a set of qualities that will empower us to uplift you.

What does AI/ML mean for us?

Our company is operating on a theme that we call Level Up! Every aspect of our business is being pushed to perform at a higher level. The notion applies to us, our platform, partners, and our approach to customer engagement.

Further, it means leveling up the work that our customers do- making their goals and missions our own. Through them, we will work towards uplifting communities and causes.

We believe that Automation, Integration, Monitoring, and Learning are key to achieving this.

Automation

Automation helps us present a tested and unified recipe in the form of a customer or donor profile. The process involves taking bits of data or ingredients in varying proportions from different sources and orchestrating them into a comprehensive profile. Our profiles can help you understand a person’s capacity, propensity, and intent.

 Automation also helps ensure that you are always working with the latest information. This reduces the margin of error and acquisition costs. We automate the most manual, error-prone aspects of the process through Artificial Intelligence.

For instance, if you are a bank you can go beyond generic service offerings. An updated profile allows you to offer products based on current life stage and needs.

Integration

We take efficiency one step further through integration. Having updated profiles is great, but if we can provide this to you within a familiar platform, it is even better!

 Our Salesforce connector app is one such integration. It allows you to see richer data on each profile within the ecosystem that you already use.

 Integration reduces your effort and helps you focus on driving engagement.

Monitoring

Monitoring enables the platform to automate and provide a seamless user experience. It provides insights that help us enhance the profile frequently. The process also helps us refine our integrations for each sector.

For instance, giving history may be a top data point for a nonprofit. The same data point may be nothing more than an interesting side note for a luxury marketer. Monitoring powered by Machine Learning creates a tailored experience for you. When you access the platform, you will see a dashboard built on data and features that are most relevant to you.

Learning

Nothing is more important than continuous learning. We are interested in two types of learning. Insights at the platform level can help enhance your experience continuously.

At a higher level, we keep our eye on about global wealth, charitable giving and macroeconomic trends that could affect you. This helps us champion your causes and thereby level-up communities.

Leveling Up Together

Artificial Intelligence and Machine Learning enable us to offer relevant and updated insights. Our focus on Automation, Integration, Monitoring, and Learning empowers your prospect engagement.

When engagement and personalization come into greater focus, corporations can better serve customers. These customers can better support causes. This means that we each help the other to level up!

Learn More

Learn more about how you can use Artificial Intelligence to test and refine your email marketing strategy.

Download our best practices guide now–>

Customer Segmentation Models for Increased Conversion

customer segmentation models

As a marketer, you are well aware of the power of customer segmentation analysis. However, segmentation is not an end in itself. Its impact grows exponentially with customer segmentation models. These models can increase personalization and engagement.

Importance of Customer Segmentation Models

Personalization is going to be a major theme in marketing. Tailoring the experience to your customer’s interests makes your message resonate. Robust customer segmentation analysis is the foundation for personalization.

In a diverse marketplace, organizations need deeper insight into demographics, lifestyle, and interests. To this end, customer segmentation models help you understand the nuances of the market.

Once you create main segments, you can analyze them further to improve personalization.

For instance, let’s say you’re a luxury car dealership based in suburban Chicago.  You are looking for customers with the capacity to spend over $50,000 on their next car. There are more indicators than a prospect’s wealth score.

You can identify prospects who live in zip codes within a certain radius of the dealership. The next step is to filter for prospects who already own a luxury vehicle. You can refine this segment further by identifying who owns your brand. This helps you determine if they are due for an upgrade or if they are looking at other luxury automakers.

You can then personalize your message in a way that speaks to each micro-segment. You can have one message for those who are loyalists to your brand. For those who own other luxury cars, your messaging could focus on comparative statistics. Focusing your marketing budget on targeted micro-segments reduces costs. Further, it also increases the likelihood of conversion.

Customer Segmentation Analysis

Segmentation models reveal patterns that help you increase engagement within these micro-segments. They also enable you to personalize marketing at scale.

WE Analyze, our analysis and modeling solution can create such models from your data. In the previous instance, you found your micro-segment. Chicago area millionaires who have a net worth of at least $5 million. You narrowed your list down further to those who own luxury cars. You then divided them into a group that owns your brand and a group that doesn’t.

Customer segmentation models can identify patterns of traits within this group. You can then apply these patterns to your database to find more prospects like your chosen segment. A customer segmentation analysis can also help to drive predictive prospecting. This includes finding lookalike prospects that match the profile of your best customers.

Customer Segmentation Models and Personalization

Customer segmentation analysis helps to drill down into smaller sub-segment to fine-tune messaging. A personalized message that reflects customer interests is more likely to resonate. If your customer relates to the message then he is more likely to engage with the brand or cause.

For example in your micro-segment, you can create smaller groups of prospects based on age and type of pet. 

This will help you personalize your pitch to them. Further, it can guide you when selecting a medium that is most effective for each subgroup.

Segmentation Analysis and Lifetime Value (LTV)

Customer segmentation models increase engagement over time. This results in improved customer LTV. Which means that the customer stays connected to the organization. LTV is a great metric for you to rank your prospects.

Prioritization means your budget and message focus on the most responsive segments. Thus, your efforts will see increased conversion at reduced costs.

Segmentation Analysis and Models are Cyclical

The more you use customer segmentation analysis and modeling the better it is for conversion. We have already established that micro-segmenting helps personalize your message and increases engagement.

Therefore, increased engagement results in higher conversions and lower costs. The other important attribute of these models is that they learn to get better over time. Every customer segmentation model helps WE Analyze learn from it. Your models become more refined, thus creating better segments for your next campaign.

customer segmentation analysis

Increase Conversion Rates

Learn more about how WealthEngine’s data science team can help you increase conversion rates through customer segmentation models. Get insights now.

Further Reading

Why You Need a Concierge Marketing Strategy

What is Wealth Screening – and How to Use it to Generate More Money

 

How to Calculate Donor Lifetime Value to Predict Future Donations

donor lifetime value

Knowing donor lifetime value for each of your contacts can make your nonprofit fundraising efforts go much faster. You can use it to forecast the future giving of your constituents. Here’s how to calculate donor lifetime value, which can help you determine which donors to nurture more closely.

What is Donor Lifetime Value?

Donor Lifetime Value is an estimate of how much you can expect a particular donor to contribute to your organization over their lifetime.

There are many factors that go into calculating what this number should be. Not only should you take into account a donor’s wealth indicators but you should also look at their propensity to give to related causes.

One WealthEngine client found that by simply asking a specific 1% segment of their donors to contribute just $100 more in a year, they would generate over $200,000 in additional funds. In five years, this would generate more than $1 million in new funding from “underperforming” donors.

The beauty of creating such a model is that it can pinpoint exactly who to target and what your ask amount should be.

Creating a Donor Lifetime Value Model

The donor lifetime value wealth model takes into account the giving history to your organization, donation frequency, contributions to similar organizations, and other factors.

WealthEngine’s deep insights into donation habits start with financial data about a donor to determine their giving capacity. The model then uses philanthropic, demographic and lifestyle data as part of the data set to predict how much a donor is likely to give.

Aside from these factors, our data science team uses our proprietary database, which has profiles on over 250 million Americans, to calculate the donor lifetime value.

These insights can help you estimate the churn risk and future giving behavior of your existing donor base.  Armed with this information, you can maximize fundraising ROI across the donor’s lifetime instead of focusing only on your next campaign.

How WealthEngine Predicts Future Donations

WealthEngine’s methodology uses machine learning techniques to determine donor lifetime value.

  1. We start with randomized partitions of known giving history. Some segments of this data are used for calibrating the model and others are used to validate it. We also evaluate various types of predictors using the data sets our clients provide.
  2. Then, we apply machine learning algorithms that iterate and learn from each round of data analysis.
  3. Once the model is created, we cross-validate it to view the model performance. This gives an overall confidence level in the donor lifetime value model.

Using a Donor Lifetime Value Model

Using these machine learning techniques, WealthEngine helps nonprofits determine very useful insights like:

  • Churn likelihood: probability that the customer will not donate anymore after their last donation
  • Next gift amount: expected amount of the donor’s next donation
  • Future gift count: expected number of donations within a 20-year period
  • Future gift total: expected dollar value of donations within a 20-year period
  • Total Donor Lifetime Value: Past plus expected future donation amounts

Equally important, the donor lifetime value model can help you identify the high-value donors at risk, including those with:

  • Moderate-to-high churn likelihood
  • High expected next gift amount or future gift total

When you know these valuable insights, you can identify approaches to increase the number and amount of gifts from your donors. You will know the potential for donor fatigue that occurs due to frequent contribution requests. This can generate higher conversions while saving your marketing investments.

Calculating Donor Lifetime Value for Your Nonprofit

WealthEngine offers multiple donor lifetime value modeling options. In addition to custom models, our popular 4-pack of pre-built models can shine a light on specific major gifts, planned giving and other opportunities within your existing base of donors.

Learn more about how to calculate and apply donor lifetime value to accelerate fundraising for your nonprofit. Take a minute to fill the form on the right and a WealthEngine rep will contact you very soon.