Marketing Uplift & Predictive Modeling

Marketing Uplift(aka Marketing Lift) and Predictive Modeling are hot concepts in marketing. In this post we take a quick look at these marketing techniques.

Marketing UpliftMarketing Uplift(aka Marketing Lift) is the difference in response rate between a treated group and a randomized control group.

Marketing Uplift Modeling can be defined as improving (upping) lift through predictive modeling.

A Predictive Model predicts the incremental response to the marketing action. It is a data mining technique that can be applied to engagement and conversion rates.

Uplift Modeling uses both the treated and control customers to build a predictive model that focuses on the incremental response.

Traditional Response Modeling only uses the treated group to build a predictive modeling. Predictive Modeling separates the likely responders from the non-responders.

Traditional Response Modeling segments an audience into the following primary groups:

  • The Persuadables : audience members who only respond to the marketing action because they were targeted
  • The Sure Things : audience members who would have responded whether they were targeted or not
  • The Lost Causes : audience members who will not respond irrespective of whether or not they are targeted
  • The Do Not Disturbs or Sleeping Dogs : audience members who are less likely to respond because they were targeted

The only segment that provides true incremental responses is the Persuadables.

Because uplift modelling focuses on incremental responses only, it provides very strong return on investment cases when applied to traditional demand generation and retention activities. For example, by only targeting the persuadable customers in an outbound marketing campaign, the contact costs and hence the return per unit spend can be dramatically improved.

One of the most effective uses of uplift modelling is in the removal of negative effects from retention campaigns. Both in the telecommunications and financial services industries often retention campaigns can trigger customers to cancel a contract or policy. Uplift modelling allows these customers, the Do Not Disturbs, to be removed from the campaign.


Big Data & Psychometric Marketing

Psychometrics, sometimes also called psychographics, focuses on measuring psychological traits, such as personality. Psychologists developed a model that sought to assess human beings based on five personality traits, known as the “Big Five.” Big data correlated with personality profiles allows for accurate psychographic targeting by marketers.

Psychometric Marketing

Psychometrics is a field of study concerned with the theory and technique of psychological measurement. Psychometric research involves two major tasks. 1. The construction of instruments. 2. The development of procedures for measurement. Practitioners are described as psychometricians. The most common model for expressing an individual’s psychometric personality are the Big Five personality traits.

5 Personality Traits (Big Five)

  • Openness (how open you are to new experiences?)
  • Conscientiousness (how much of a perfectionist are you?)
  • Extroversion (how sociable are you?)
  • Agreeableness (how considerate and cooperative you are?)
  • Neuroticism (are you easily upset?)

Based on these 5 dimensions, also known as OCEAN(Openness, Conscientiousness, Extroversion, Agreeableness, Neuroticism) we can make a relatively accurate assessment of a person. This includes their needs and fears, and how they are likely to behave.

The “Big Five” has become the standard technique of psychometrics. The problem with this approach has been data collection, because it required filling out a lengthy, highly personal questionnaire.

With the Internet, and cell phones this is no longer a problem.

The Internet allows researchers to collect all sorts of online data from users and using Data Correlation they can associate online actions with personality types. Remarkably reliable deductions can be drawn from simple online actions. What users “liked,” shared or posted on Facebook, or what gender, age, place of residence they specified can be directly correlated with personality traits.

While each individual piece of such information is too weak to produce a reliable prediction, when tens, hundreds, or thousands of individual data points are combined the resulting predictions become very accurate. This enables data scientists and marketers to connect the dots and make predictions on people’s demographic and psychographic behavior with astonishing accuracy.

Smartphones are a psychological questionnaire on their users that is constantly being updated, both consciously and unconsciously. It is not uncommon for data analytics companies to have over 4,000 data points for each person in their target data set.

The strength of their psychometric modeling was illustrated by how well it could predict a subject’s answers.

It is now possible to assign Big Five values based purely on how many profile pictures a person has on Facebook, or how many contacts they have (a good indicator of extroversion).

Psychological profiles be created from this data, but the data can also be used the other way round… to search for specific profiles.

This allows for accurate psychographic targeting by marketers in ways that have never before been possible.

BriteWire Intelligent Internet Marketing facilitates building Psychometric User Profiles with purposefully designed content interactions, and automates marketing responses based on those triggers.


Google AdWords Industry Benchmarks for Real Estate

Google AdWords Pay Per Click(PPC) remains the most widely used online advertising system. Advertising Return On Investment(ROI) is easy to calculate for AdWords. To plan your marketing budget, and set some goals, it is first important to understand the benchmarks for your industry.

Google AdWords Industry Benchmarks for Real Estate

Here are the important Google Industry Benchmarks for the Real Estate industry.

Metrics covered in this article are:

  • Average Click-Through Rate (CTR) in AdWords for Real Estate, for both Search and Display
  • Average Cost per Click (CPC) in AdWords for Real Estate, for both Search and Display
  • Average Conversion Rate (CVR) in AdWords for Real Estate, for both Search and Display
  • Average Cost per Action (CPA) in AdWords for Real Estate, for both Search and Display

Real Estate Average Click Through Rate for AdWords

The average click-through rate (CTR) in AdWords across all industries is 1.91% on the search network and 0.35% on the display network.

For the Real Estate industry the average CTR is 2.03% for search network and 0.24% on the display network.

Real Estate Average Cost Per Click for AdWords

The average cost per click (CPC) in AdWords across all industries is $2.32 on the search network and $0.58 on the display network.

For the Real Estate industry the average CPC is $1.81 for the search network and $0.88 for the display network.

Real Estate Average Conversion Rate for AdWords

The average conversion rate(CVR) in AdWords across all industries is 2.70% on the search network and 0.89% on the display network.

For the Real Estate industry the average CVR is 4.40% for the search network and 1.49% for the display network.

Real Estate Average Cost Per Action for AdWords

The average cost per action (CPA) in AdWords across all industries is $59.18 on the search network and $60.76 on the display network.

For the Real Estate industry the average CPA is $41.14 for the search network and $59.06 for the display network.

* This data is accurate as of January 2017.

Category : BriteWire Blog


Performance Problems With Current Real Estate Technology

Real estate brokerages and real estate agents are investing in solutions to increase sales by delivering a richer and more effective real estate experience. They are attempting to create the next generation of real estate brokerage. In the process they are learning they are not always getting a positive return on their investments in technology.

Performance Problems with current real estate technology-thThere are numerous technology platforms and tools currently available to assist real estate professionals. Tools exist to support the entire lead generation, lead management, and sales process.

Many of these tools are sold using on-demand SaaS(Software As A Service) business models. SaaS business models allow customers to access technology solutions without owning the infrastructure, technology, and people required to develop, deliver, and support them. Providers of these tools for the real estate industry make dramatic performance claims of increasing sales while reducing total cost of ownership.

However, these tools do not seem to be performing as expected. Despite the availability and investment into real estate sales tools, technology, and automation – all indications are that the return on investment from those tools is falling short. Individual performance of real estate professionals has not increased as a result of these tools.

My personal experience in creating technical solutions for over 25 years is that you can give a person a tool, a wonderful software solution, but you can not give them the creativity, drive, and years of first hand experience needed to use it effectively.

As real estate brokerages and real estate agents attempt to effectively use these tools, they are quickly realizing they need help.

They are learning you can’t just purchase a CRM solution like Sales Force, or a marketing automation solution like Marketo. You have to properly integrate it into your business processes. You have to develop marketing strategies that utilize these tools, and create content that interfaces with the tools. You need years of experience to know what works, and what does not.

The challenges real estate brokerages and real estate agents are having generating successful results with tools sold using the SaaS business model has led to the creation of a new business model; Service As A Service.

These companies are taking a traditional SaaS model and turning it into a true ‘Service As A Service’ business model uniquely suited to on-demand and cloud technology solutions. These new Service As A Service companies are characterized by:

  • A deep understanding of the needs of customers.
  • Comprehensive knowledge of the technology solutions that make sense for each individual customer.
  • The ability to bundle or package existing solutions to create custom solution stack.
  • An ability to combine technology and best practices in efficient, effective ways to deliver a competitive advantage for their customers.

On-demand SaaS business models were a good first step solution for the vast majority of customers who really should not be owning and operating their own Information Technology. The various solutions can be “pieced together” to create end to end solutions, but it is expensive and frequently not effective or efficient.

Service As A Service real estate solutions will play an important role ensuring that brokerages and agents get maximum advantage from innovations in technology.

Category : BriteWire Blog


PropTech Disrupting The Real Estate Industry

Real Estate is the largest and most valuable asset class in the world but the Real Estate industry is ripe for disruption. Traditional real estate brokerages are under increasing competitive pressure as technology companies make inroads into the previously walled off real estate market. This complex, multi-faceted and high-stakes industry is rapidly becoming one of the hottest markets for entrepreneurs and investors alike.

Proptech - Fintech

PropTech(short for Property Technology) refers to the sector of startups and new technologies cropping up in response to decades of inefficiencies and antiquated processes in the real estate industry. The term is being used to encapsulate the entire market space of technology and real estate coming together to disrupt the traditional real estate model. PropTech is also referred to as CREtech (Commercial Real Estate Technology) or REtech (Real Estate Technology).

The PropTech sector is generating increased buzz as more people realize the opportunities for innovation in this sector, and venture capital investments expand. Real estate tech startups around the globe raised $1.7 billion worth of investments in 2015 – that’s an 821% increase in funding compared to 2011’s total. PropTech companies have raised around $6.4 billion in funding from 2012 to 2016. It is difficult to pin down exact numbers, but it is estimated that investment in the space increased by 40% for 2016. Compass, Homelink, SMS Assist and OpenDoor Labs all saw their valuations increase to over $1 billion in 2016.

Internet technology has tremendous potential to improve transparency and efficiency in real estate transactions. Property Listings and Property Search was the initial area for improvement. Over the past several years, technology advancements in property search and listing engines have been introduced.

These advancements allow home buyers to more easily find their home by making search criteria easier to specify. Buyers can specify the obvious search criteria like price range, size, number of bedrooms, and location. Additional facets of navigation like lot size, water features, adjacent public land, conservation easements, and if horses are allowed can also be used as search criteria. Buyers can view maps of where the homes for sale are located, and find homes for sale using maps as their primary search navigation tool. Search criteria can be saved in property search engines so that when new homes come on the market that match a buyer’s predefined criteria they are automatically notified.

Advancements on property listings have allowed a listing to easily be syndicated to hundreds of websites with the click of a mouse. This dramatically expands the listing’s exposure to potential buyers.

Technological advancements in deep learning, AI and other big data technologies are driving significant innovation in all areas of the property technology sector. Advancements in video, 3D Modeling, and virtual reality are allowing buyers to virtually tour homes they are interested in. These advancements allow agents to more effectively showcase the properties they are selling. However, these advancements in moving key data to the Internet may also mitigate the role that real estate agents play in the real estate process.

Competition in the space is increasing, but many tech companies do not have access to the industry and associated data due to real estate laws and regulations on disclosure. In many states it is illegal to disclose the price of a real estate transaction, and only members of the local real estate MLS have access to all the listing information.

What is next? Investor confidence is high and reports are that a massive amount of investment capital will be pumped into the real estate sector. It is safe to assume that we will see significant changes in the technical landscape for the real estate market.