Analytics is the process of collecting and analyzing data to produce customer insights, optimize marketing campaigns and create operational efficiencies within an organization.
As marketers in the building product industry, we get excited about data analytics because it can provide insights about homeowners that traditional marketing methods cannot capture.
For instance, building material manufacturers are using data analytics to determine which building products resonate with homeowners and turning these insights into action by deciding where to target their marketing dollars for the best ROI.
But unfortunately, not all building material companies are equipped to interpret data analytics.
At Renoworks, we see a virtual goldmine of untapped data at many building material companies’ fingertips.
Here’s how we think the building material industry should evolve to embrace data analytics, and some of the key performance indicators to start paying attention to:
Product Interaction and Engagement
The building material industry has traditionally relied on brochures, photographs, samples, swatches and show rooms to provide product interaction experiences to homeowners.
One problem with the traditional method is that convenience is becoming more important to homeowners. Many homeowners won’t travel more than a few kilometres to attend a showroom when the internet provides them with almost everything they need.
Driven by the extreme convenience offered by platforms like Amazon, Skip the Dishes and Uber, homeowners have grown to expect the same level of convenience from other industries.
Consumers now expect convenient and enjoyable digital product interaction experiences.
Another problem is that it’s difficult to get quantitative data on how much time a homeowner spends looking at a product sample and which combinations of building materials they interacted with the most.
Digital product interaction experiences (like visualizers, product libraries and configurators) solve these problems because they allow homeowners to interact with building products at home. They also enable marketers to automatically track important key performance indicators such as Engagement Rate (ER) and Building Product Interaction Frequency (PIF).
This digitally-recorded engagement information gives building material marketers important information that they can use to:
- optimize color and product combinations in marketing collateral;
- inform product decisions;
- design physical samples for dealers and contractors that are informed by quantitative data; and
- better understand the homeowner’s “buyer journey” on the company’s website.
Digging even deeper, a building material marketer could combine customer demographic data from other sources (like a visualizer sign-up form) to make a data-driven determination of the building product combinations that appeal most to different demographics of homeowners.
Those product combinations could then be marketed more heavily in regions that contain the ideal customer for that particular combination of roofing and siding product.
Improving Customer Personas
A “customer persona” is a fictional representation of a company’s ideal customer based on assumptions, experience with customers and hard data. Marketers often prepare a customer persona document to share within their organization in order to keep everyone apprised of exactly who their ideal customer is.
But in the building material industry, these customer personas are often based on anecdotal data from sales reps, outdated information or assumptions.
Analytics data from a building material company’s website and visualizer can help improve customer persona documents by providing factually-based insights into ideal homeowner behaviour, demographics and preferences.
For example, when a homeowner signs up on a building product visualizer or configurator, they often provide important details like their name, email and zip code. Combine these details with data on high-value homeowner users (e.g. high ER and PIF scores) and new insights can emerge.
Maybe homeowners from a particular suburb that is becoming “gentrified” (i.e. younger homeowners replacing an older demographic) have higher ER scores and tend to convert to customers easily once you refer them to your preferred contractors.
This quantitative data could be used to design a marketing campaign that is targeted at similar neighborhoods across the US and Canada.
Without the quantitative data and key performance indicators as back-up, it may be hard for building material marketers to justify such a large campaign.
However, the analytics data can provide more assurance that the campaign will be successful.
Marketing Automation and Lead Scoring
The sales process in the building material industry tends to rely very heavily on attendance at trade shows, cold calls, emails and other “high touch” sales techniques.
It’s a process that works well, but technology can now help significantly.
Marketing automation technology can give a single building material marketer the power to accomplish work that would have required an entire marketing department 10 years ago. This is very important in light of the pressing need for efficiency in the new home construction and remodelling industry.
Part of the reason marketing automation is so powerful is because it can automatically qualify a lead and push them down a specific sales path depending on how high they “score” on a list of factors. These lead score factors include behavior, demographics, social data and interaction with your building products, website and marketing content.
A marketing automation system that combines analytics data from several sources can automatically identify a high-value lead and place them on a customized path that is more likely to convert them to a customer.
The factors that result in a higher lead score are different for each building material company, but could include Loyalty Rate (LR), number of website visits, engagement with certain building products or reading a certain blog article.
For example, if a homeowner returns to a website several times (high LR score) and has gone through several product combinations, it may be the right time to send them an email offering the assistance of a preferred contractor to help them move their project forward.
Marketing automation can be set up to automatically push a notification telling a sales rep to follow up with a customer in such a situation. Its all part of making a more personalized experience for a homeowner.
Software like Hubspot can even be configured to show different “calls to action” on a website depending on a visitor’s lead score, so that a homeowner who has only visited your site once might be urged to read a blog article and a visitor who has visited your website several times can be asked if they want to be contacted by a preferred contractor or sales rep.
This type of marketing and sales automation helps manufacturers and distributers with sales and drives highly-qualified leads to preferred contractors.
Predictive Data Analytics
Predictive marketing is perhaps one of the most exciting uses for analytics data, and many companies are starting to build sophisticated models of customer behaviour based on their data resources.
Building material companies can aggregate and analyze data from sales, CRM’s, website visualizers and other sources to identify the digital behaviours that occurred right before their customer made a purchase. A model can then be built using data science methodologies to inform their marketing and sales strategy.
For example, the data may show that a building material manufacturer’s highest-value homeowners (e.g. high ER, PIF and LR scores) tend to search for specific keywords on Google or follow certain social media accounts related to home improvement a few months before making a remodeling decision.
This digital behaviour could trigger a targeted ad campaign designed to get your building material brand in front of the homeowner early in their remodelling journey and drive them to your website, visualizer or product configurator.
Predictive marketing becomes even more powerful with the continual improvement of digital advertising tools like Facebook’s “lookalike audiences”, which gives building material companies the ability to take analytics data on their ideal homeowners and advertise to thousands of other homeowners with similar attributes.
But the value of data analytics isn’t just limited to optimizing sales and marketing campaigns. It can also be used to create operational efficiencies that save building material companies time and money.
For example, construction giant JE Dunn partnered with Autodesk to develop a system for predictive modelling of operations. The “LENS” estimation system combines with Autodesk’s FORGE technology to create a single source of truth about a project that enables better project insights and decisions.
The Future of Analytics for the Building Material Industry
Technology is quickly advancing to allow building material companies to integrate their own data with outside data to improve their product offering, make better assumptions about their ideal customers, qualify leads with real data and make predictive models.
The analytics data that drives these efficiencies can come from multiple sources, such as Google, social media, sales records, CRM’s and marketing automation software. Visualization platforms are also an important industry-specific source of analytics data to track important metrics such as Engagement Rate, Building Product Interaction Frequency and Loyalty Rates.
Of course, the best analytics solution will depend on the specific situation and data mix of each building material company.
But one thing is for sure: The companies that invest in data analytics early will be well positioned for the future.