On the face of it, Google’s new click-to-message ads are a natural development of their search offering – adding another opportunity for brands to engage with their customers on top of existing ad extensions like Click-to-Call, and Location which allow potential customers to choose their preferred mode of communication.

It’s notable that this product launch comes at a time when the rise of mobile and text-based messaging as a communications channel is experiencing significant development and growth. Facebook data suggests there are over one billion messages sent each month to businesses on the platform so it’s not surprising that Google is enabling a feature that consumers are already actively engaging in.

For brands looking to improve the way they connect with customers on a more personal level, there are some significant opportunities. Many brands already communicate with customers on social platforms and via live chat on site, typically this is customer service led – and there is significant value in communicating directly with customers in a more personal and human way – both in better understanding customer needs, and in tailoring solutions to their needs. The click-to-message feature now enables brands to start this conversation directly from the search page at the moment when potential customers are actively researching products and services enabling a more personal touch that could be more suitable to converting a potential customer into a sale – particularly in more service led industries.

The learning curve 

The changing nature of the consumer-brand relationship to greater one-to-one communications has implications for brands too in their ability to service customers quickly and effectively, the importance of which is no more urgent than at the point of search – customers are expecting immediate and fruitful responses to their requests. We, therefore, envisage significant growth in the automation of these communications, requiring new skills of agencies and brands in deploying technology that understands natural language from customers (NLP – Natural Language Processing). 

This technology will also have to create complex decision trees to respond to customer needs instantly, maintain brand identity and adapt to the customer personally (AI), while still deferring to humans when necessary. With growth in text communication, brands that succeed will harness this rich source of data for brands in understanding their customers to better tailor products, services, and solutions to their customers.

It’s already possible to see the growth in the automate messaging communications, with Facebook launching the Messenger Platform back in April which enable brands to launch bots for Messenger. It opens up opportunities for brands for customer service, content engagement and e-commerce (payments recently launched in the US). Albeit while many bots at this stage are fairly rudimentary in form with simple decision tree’s and limited scope of functionality, we envisage these to get more complex and full-featured as brands and agencies expand their capabilities.

Google’s launch of its click-to-message in search, personal assistant on Android, along with Allo, the smart messaging app  on IOS and Android in recent months are real demonstrations of Google evolving its search capabilities to be more personal in the way they can connect customers with information to rival Facebook’s already well-established messenger platform – we expect more product innovation and developments in this space as Google, Facebook et el look to establish the ecosystem that consumers adopt in their communications with information and brands.

It’s difficult not to mention the newly launched Google Home, Amazon Echo and other voice personal assistants as part of the same ecosystem – where customers use voice to query, with audio responses – the same automation and logic applies to this space, and highlights the importance for brands to begin to develop their capabilities to exploit all platforms, both text and voice based; understanding complex customer queries, and automation in response.