Category: <span>Artificial Intelligence</span>

RT3 Member Cognitive Contractor Launches Data-Driven Customer Acquisition Solution for Contractors

The company delivers industry-specific sales & marketing technologies backed by the science of data.

FOREST HILL, TEXAS (PRWEB) FEBRUARY 17, 2021

Cognitive Contractor, a pioneer in the application of data-driven customer acquisition solutions to the contractor industry, formally launched its end-to-end sales and marketing solution to the roofing and solar sectors.

Developed by roofing, construction, and technology entrepreneur Josey Parks, this purpose-built solution helps companies prioritize their sales and marketing efforts to focus on the leads that are most likely to become customers.
“Our technology can accurately predict your next sale,” explained Parks. “Now, sales teams are equipped with the knowledge they need to ensure they are knocking on the right doors and not wasting valuable sales hours or marketing dollars on people who will never convert. We also back their sales efforts with multi-channel marketing campaigns that pre-set appointments, so sales reps just have to show up and close. And every campaign is tracked, reviewed, and refined, to continually improve results.”

Cognitive Contractor uses data analytics to build profiles of a contractor’s ideal core customer. Their AI-based technology uses this information to analyze the market and predict which leads are most likely to buy. Leads can also be filtered based on their highest potential value or lifetime value to hit specific revenue goals. When combined with the company’s highly targeted and personalized multi-channel marketing campaigns, contractors report closing rates that increase by double digits.

The company’s analytical approach to data-driven lead generation and engagement produces powerful sales numbers for contractors who use the solution, including Parks’ own companies. “Data is powerful. When you analyze your customer base, you can identify common attributes among your best performing customers. Then, you can use that customer profile to identify similar targets in your market,” Parks explained. “Cognitive Contractor is far more advanced and deliberate than traditional lead generation services, where sales teams scramble to respond first—even when a lead doesn’t fit the company’s ideal customer profile. We are leveraging technology to help contractors be more strategic and successful in their prospecting efforts.”

Steve Soule of CMR Construction & Roofing said, “Cognitive Contractor has completely changed the trajectory of my company. They have transformed our entire approach to customer acquisition to be targeted and refined. Data-based insights from Cognitive have charted our course, and their continuous guidance has brought us even further than I could have imagined.”

About Cognitive Contractor
Cognitive Contractor delivers industry-leading, data-driven customer acquisition, sales, and marketing technology to the contractor industry. By leveraging the power of big data, analytics, AI, and machine learning, they help contractors predict their next sales, convert leads to appointments, and exceed revenue goals. Born from a pressing need for better sales & marketing solutions in the CEO’s roofing and construction companies, Cognitive Contractor’s team of industry experts and data scientists have a deep understanding of the problems that contractors face and are uniquely positioned to solve them. Learn more at http://www.cognitivecontractor.com.

RT3 Members Present on Data and AI at METALCON

By Karen L. Edwards.

METALCON 2019 took place in Steel City – Pittsburgh, Pennsylvania and RT3 members were well represented at the show, exhibiting and speaking.  On the first day of the show, RT3 hosted a discussion on the importance of artificial intelligence and utilizing data for contractors.

Bill Wilkins of Pointivo spoke about AI and explained that there are a number of companies that offer AI-assisted approaches to roof evaluations.  His company has been working with another RT3 member to develop a system that will do just that. Bill explained asking a person to try to look at an image and identify drains, equipment, ponding water, areas of membrane splits, etc. can be a very time-consuming process.  Ai is a great opportunity to help augment a younger , more inexperienced work force in identifying rooftop conditions and problem areas.

AI can tell you what it thinks is on the roof and provide a confidence level in its identification. How you help is by looking at what it found and either confirming it or correcting it. Each time you provide confirmation or correction, it will learn from the information and keep getting better at what it does. Bill explained that they feel pretty confident that the tool they are introducing next year will be able to reduce the amount of time spent on evaluations by 80 percent through the use of drones and AI.

Key things for AI to be successful is quality data, quantity of data. Bill shared the example of teaching AI to recognize on AC unit on a roof. Because an AC unit is so large, it might only need to ‘see’ 100 images to be able to accurately identify the AC unit every time. Trying to identify hail damage will be harder, because it’s much smaller in size.  The more data, imagery and confirmations it receives, the smarter and faster it becomes.

Josey Parks of Cognitive Contractor shared how AI and data can be a powerful lead and  sales tool for roofing businesses. Josey explained that if you take the records for 1,000 customers and run them through an AI program it will learn from the data. It will recognize patterns of the first 70 percent (or 700 records). Then it will take the next 300 records and predict their behavior based on what it learned from the first 700 and provide them a score.  Contractors should understand the data that they have in their business and how they can structure it to understand what drives your business and your customers.

Josey explained how when he started in metal roofing, he would keep track on a paper of what neighborhoods he had knocked doors in, then he advanced to using a bike trail app to track the locations where he and his sales team had been. They have advanced today to sending emails and plotting on a map (like Google Earth) the locations of the people who opened the email. This allows the canvassers to have an optimized route to work from.

Taking it one step further with the advancement in technology, Josey explained that he is able to use AI to score and predict his leads to the point that it knows which salesperson is the best one to assign that lead to, based on past performance of the sales person.  It’s important to optimize your business and not waste time and resources assigning the wrong leads to the wrong salesperson.

If you missed their talk at METALCON, you can watch it on our Facebook page under Videos.  Be sure to sign up for the Smart Brief e-newsletter to get the latest roofing tech news in your inbox.

 

Study suggests autonomous robots working together are the industry’s next big thing

By Karen L. Edwards.

Collective robotic construction (CRC) specifically concerns embodied, autonomous, multirobot systems that modify a shared environment according to high-level, user-specified goals.

A Science Robotics study published this March states that ‘the increasing need for safe, inexpensive, and sustainable construction, combined with novel technological enablers, has made large-scale construction by robot teams an active research area.’

The study notes that 54% of the human population currently live in cities and that number is expected to grow to 66% by 2050. The researchers feel that collective robotics can help meet the construction demand in the midst of an ongoing labor shortage. CRC could also make construction safer for workers, with the Department of Labor citing that 20% of all worker injuries occur in construction.

The researchers were inspired by the extensive use of collective construction in nature for building nests, protection barriers, traps and mobility scaffolds. Where animal construction relies on reactive behaviors and ‘low-bandwidth communication,’ robots can rely on high-resolution sensors, high-speed communication and GPS to communicate their exact location for completing specific tasks.

Construction materials used in CRC are divided into two categories – discrete and continuous. Discrete materials would be square, rectangular or homogenous bricks, struts and sandbags. Continuous materials would be things like two-component foam, concrete and fibers.

The study says that “challenges pertain to CRC hardware, especially in relation to coordination, communication, and multimodal sensing.” The robots need to be able to adequately communicate and coordinate with nearby robots for success. “As more advanced sensors such as radar, depth cameras, laser imaging and ranging systems, and GPS become cheaper and more readily accessible, they may play a bigger role in the field. ”

The researchers reference two published systems, UAVs and climbing robots,  that can be used to develop a metric that measures constructed volume relative to time, the number of robots used and the volumetric size of each robot. “A flying robot [UAV] has higher energy expenditure and lower payload than a climbing robot but may fly directly between material cache and deposition sites. Reversely, climbing robots can carry more but have to traverse through previous construction.”

The study is the first step in really determining how robotics can make an impact in construction. Further study is needed to develop performance metrics, evaluate the reliability of CRC and it’s ability to adapt to changes in movement, or expected behaviors of the other robots. There also needs to be more research in order to determine where humans fit into the CRC picture to oversee work, make adjustments and corrections when there is an error and in the support and maintenance of the robots.

Read the full study here. 

How Predictive Analytic Technology Can Grow Your Roofing Business

By Tony Agresta, Vice President of Marketing, Nearmap

 

Predictive analytics is not new, it’s been used by marketers for many years. It is simply using historical data on response or performance to determine who is most likely to buy a product or respond to a promotion. For example, cataloguers would take a sampling of data, send out a mailing and track who responds. The more data they had about the people such as income, age, interests, prior buying history, the better they could predict future buying behavior since the responders and non-responders could be modeled.

By scoring and modeling the data, a company could focus their dollars and marketing efforts on the people who scored highest and were determined to be the most likely to buy. Rich, accurate models leverage robust data sets.   That same concept can be applied to roofing, using modern technology, to determine the properties most likely to need roofing services.

Many roofing contractors today already understand the value that high-resolution aerial maps bring to their business. The images provide a lot of data about a property that satellite imagery cannot. For instance, using freely available satellite imagery, it’s not easy to tell the difference between a solar panel or a skylight on a roof, and it can be hard to tell what type of roofing material is on the property.

With higher-resolution aerial maps, contractors can review properties, see the type of roof, whether there are skylights, solar panels, outbuildings, the presence or absence of trees, and can even look back over time to see how the roofs may have changed.   High-resolution aerial maps provide the detail needed to classify features of the property and the grounds.  Just the way the cataloguers could use sample data to differentiate responders from non-responders or multi-product buyers from single product buyers, aerial maps can be used to create data sets that classify type of roof and other features.

When machine learning algorithms are applied to this new source of data, users can automatically detect which properties have skylights, or solar panels or missing shingles. It could detect the pitch and potentially the type of roof material. Then the algorithm could store all those attributes in a database. The database is important because now you have data about all the properties in an area that can be queried.

Querying the database would allow a contractor to ask for only properties that meet certain criteria to be returned. Perhaps you want roofs of a certain size, or ones that appear to have damage, or only want to look at roofs with asphalt shingles. You no longer must spend the time manually scanning through images of properties, the algorithm does it for you.

By assigning scores to certain characteristics and using artificial intelligence and machine learning, the database can deliver a list of leads that are prime candidates for a new roof. This allows you to strategically deploy your sales team to the homes that score the highest, rather than walking a neighborhood knocking on every door.  Companies providing aerial maps are applying machine learning to vivid imagery. They are refining the algorithms, building accuracy into the models and making the resulting data available to roofers to help drive their business faster.

Study Finds Construction Industry Can Benefit From Artificial Intelligence Adoption

A McKinsey & Co. study on artificial intelligence (AI) applications in the construction industry reports a combined use of machines and digital technology can enhance quality control, project scheduling, data analysis, and project cost savings, according to www.constructiondive.com.

The construction industry currently is the second-least digitized economic sector in the world, and the industry needs to lay the groundwork before AI can be widely adopted. The study identifies investment in data collection and processing tools like cloud infrastructure and advanced analytics as the first step.

There has been increased interest in sensors, cloud-based data sharing and mobile connectivity within the construction industry. Some employers already are using wearable sensory devices to monitor workers’ location and equipment at worksites. Data collected from the devices is transmitted to a cloud-based platform accessible from any compatible mobile device. AI algorithms advance the process one step further by deploying real-time solutions based on data analysis, helping employers ensure their workers stay safe on the job.

Industry employers may look to other industries that have successfully used AI to optimize processes, including the pharmaceutical and healthcare industries. The study notes an AI algorithm is used by the pharmaceutical industry to predict medical trial outcomes; a similar algorithm may be used by the construction industry to forecast project risks and constructability. And image recognition algorithms used by the healthcare industry to support diagnoses may enable drones to assess construction site images for signs of defects or structural failures.

Note: This article first published on the NRCA website and can be viewed here.