Buying a home in the 1980s was a very different experience to what it is today. The typical homebuyer would meet with a real estate agent, describe their ideal home, neighbourhood and price range, and then rely on the broker’s knowledge of the local market to match their requirements against a selection of properties. After a number of visits, inspections and possible refinement of the homebuyer’s search criteria, a suitable match might be made, leading to negotiation of the offer price and closing conditions.
Today, the experience is different largely because the typical homebuyer does an inordinate amount of online research before their first meeting with an agent. To narrow the field to a few suburbs and home options, they might check property records and details, local real estate trends, recently sold homes, historical sales transactions, and any other public information they can find. What this means is that the typical homebuyer of today is far more educated and sophisticated than their predecessor of a few decades ago.
This concept is referred to as ‘information asymmetry’, where one party in a transaction has more or better information than the other. And in the 1980s, most salespeople(not just brokers) had more information about the products or services they were selling than their customers did – in effect giving them an information advantage.
That changed with the advent of the Internet in the 1990s, when the information that once resided with the salesperson (and made them an ‘expert’ in their field) was liberated and available for all to look up and consume. As the Internet gained widespread adoption, the information asymmetry between salespeople and their customers began to shrink, then disappeared altogether, before finally moving in the opposite direction.
Today, many customers are better informed than the salespeople they engage with, largely due to the substantial amount of research they do beforehand.
This well-documented phenomenon – of information asymmetry swinging from the salesperson to the customer in recent times – is manifesting itself across countless industries, and is being compounded by another trend called ‘mass personalisation’. Better informed and educated, customers are increasingly dictating what they want and demanding a more personalised service when they buy.
They also want to deal with salespeople who educate them and provide contextually relevant information, and to not waste time on probing questions that highlight ignorance. This amplifies the pressure on sales and marketing departments, who are finding themselves on the wrong end of these trends and ill-equipped to cope. Unable to reverse the tide, many salespeople are finding their once-lucrative jobs disappearing and being replaced by self-service models, and corporate margins are under siege by well-informed consumers who shop the market for the best deals.
Today, many customers are better informed than the salespeople they engage with, largely due to the substantial amount of research they do beforehand
Where will it all lead? Enter artificial intelligence. Although much has been written about the potential loss of jobs to artificial intelligence software and robots, a far more interesting and immediate application of articifial intelligence revolves around its ability to make certain jobs more productive – in particular, within sales and marketing departments. In fact, the ability of artificial intelligence to quickly shift through very large amounts of data and convert generic information into specific knowledge, is fundamentally changing the face of sales and marketing departments in many industries.
Consider that artificial intelligence can automate the complex analytical and research tasks required to create information symmetry, and boost the return on sales and marketing initiatives through better allocation of resources and improved (ie personalised) messaging and pricing.
Large productivity gains can be achieved by directing salespeople to the most promising opportunities, arming them with customer-specific research
As an example, large productivity gains can be achieved by directing salespeople to the most promising opportunities, arming them with customer-specific research for each visit, and helping them recommend the best combination of products, services and pricing to each customer.
Without enabling technology that can automatically find the data and analyse it, carrying out such tasks on a daily basis would become highly complex and unwieldy, quickly falling into the toohard basket – especially for businesses that employ large sales teams and serve thousands (or hundreds of thousands) of customers.
However, through the use of artificial intelligence the customer data can be automatically captured, automatically analysed, and automatically delivered to a salesperson in the form of actionable insights, such as “visit this customer”, “deliver these messages and insights”, and “offer this mix of products at this price”.
By automatically providing such insights to in-field salespeople and telesales operators, productivity and yield increase because they begin targeting better opportunities, with the correct mix of products, at the optimal price point, with the customer in turn receiving a higher-quality engagement and personalised service.
Customer data can be automatically captured, automatically analysed, and automatically delivered to a salesperson in the form of actionable insights
INDUSTRY VIEW: PHIL QUIN-CONROY, EX-CEO, PLAN AUSTRALIA
While artificial intelligence might not be part of the broking world any time soon, technological advancements are already supporting brokers in many ways.
PLAN Australia’s broker platform, Podium 2.0, powered by the world’s leading CRM system, Salesforce, has been designed in direct response to the evolving needs and roles of brokers and can raise a broker’s game in the sales and marketing space.
Brokers may need to make contact with a prospective customer as many as five times before they become a client, and it can be difficult to keep track. An automated CRM system like Podium 2.0 keeps brokers up to speed on how often they are communicating with clients and can also remind them of good opportunities to touch base with them. This could include sending them personalised, automated messages such as a ‘thank you’ following settlement, wishing them many happy returns on a birthday, or offering them loan health checks on loan anniversaries.
The platform is also fully compatible with tablets, saving brokers time and allowing them to access customer data more easily while on the move.
At the time of writing Phil Quin-Conroy was CEO of PLAN Australia and a leading commentator on technological innovation in the third party channel.
AI in practice
Science fiction? It’s already a reality. As one example, Australia’s own Complexica has recently launched an artificial intelligence-based software product called ‘Larry, the Digital Analyst’, which fetches data from the internet and overlays it with existing customer data to build granular ‘customer profiles’. These profiles are then used by ‘Larry’ (think Siri, but for business) to:
find prospective customers that have the same profile as that of highly profitable customers
carry out customer-specific research to prepare salespeople for each individual conversation
provide salespeople with value-adding insights that can be shared with each customer (such as “customers just like yours are doing/buying/selling xyz at the moment” or “this is what’s selling well in your area”)
personalise the conversation by providing customer-specific offers, bundles and pricing
In their 2016 Australian Mortgage Report, Deloitte brought together brokers and lenders to discuss the impact that ‘digital warriors’ would have on broking.
ING DIRECT’s Lisa Claes defines digital warriors as “the 16–34 age group, who like to DIY, [and] may only require validation rather than delegation in their interaction with a broker”. Essentially they are the consumers who are most empowered by changing information symmetry; they can research, learn about and compare financial products before going to a broker; and they are less interested in delegating that research to a broker.
While these consumers could go straight to a bank, they will still look to a broker to validate their research. Claes believes the impact of these consumers will force brokers to move away from a purely delegator model. Deloitte partner James Hickey, who co-authored the report, noted at the launch of the report that “it may be that the broker model evolves to be more of a supplementary model for those types of customers”.
A new field of ‘automated analytics’ is emerging to deliver such advanced functionality, and companies like food distribution giant PFD Foods (with $1.6bn in revenue) and Liquor Marketing Group (with more than 1,400 retail outlets) are using it to help their sales and marketing departments generate win-win outcomes for their suppliers and customers.
They are not alone, and represent the future of sales and marketing – a future that requires sophisticated technology to tackle information asymmetry and mass personalisation head-on, and properly analyse the mountains of data created each day to find needle-in-the-haystack insights that salespeople can use with their customers.
Today, a quality product is a given – to stay truly competitive and relevant businesses need to raise their game in sales and marketing, and artificial intelligence is one of the technologies they are turning to. From banking, insurance and real estate through to manufacturing, wholesaling, and retailing, artificial intelligence is changing the way companies market their products, engage with customers and, ultimately, differentiate themselves in what has become an increasingly commoditised and noisy world.
Matthew Michalewicz is CEO of Complexica, a provider of artificial intelligence software that helps large organisations increase revenue, margin and customer engagement through automated analytics. He was named the Pearcey Foundation Entrepreneur of the Year, and made the Business Journal’s ‘40 under 40’ list of accomplished business leaders. Matthew is the author of several books, including Life in Half a Second, Winning Credibility, and Puzzle-Based Learning.