Since the late 1980s I have been fascinated by online experiences and the ways these interfaces grab our attention and drive action. From the first Public Bulletin Boards through our phone line at home in the late 80s, Mosaic and Email at university in the mid 90s, Google search in 2000, to Facebook and YouTube in the mid 2000s, then the iPhone and apps in 2008 are all examples of a natural progression. I also remember playing mobile games in the early 2010s and trying to avoid paying for progression by watching video ads. All of these have been inspirations to what follows.
Now we have so many choices that unless an online experience feels relevant and understandable, I at least, have a tendency to fall off. At the same time, these experiences also often feel so creepy that I am unsure if I am being tracked down to every click after an interaction.
It was in this context that I decided that there must be a better way to make progress. The ideas were created talking to kids and young adults - people of gen Z. Starting with my son, I soon had talked to over 200 amazing people and the conclusions were similar: Rewards & incentives, trading & exchanging these, and doing so through a gamified look and feel, were all at the core of what they expected of brand interactions. And for these interactions to garner actual attention, I understood that the format should be more dialogue, than monologue driven; speaking with the audience and not just to it. When I brought these ideas from the gen Zers and moved up on the generational chart, all the way through to baby boomers (and even later), talking to over a 100 people aged between 30 and 80 years old, the ideas continued to resonate:
Close to everybody wants to be rewarded for their interactions with brands. Moving on; these interactions need to be in a two way format and tailored for every individual, if people are to give those interactions their attention.
My vision became to provide these superpowers to all brands, and doing so by creating a platform with three core pillars catalysed by the impact between them:
Rewards x Attention x AI = 10+ x Impact
Let’s break this equation down and look at why it really matters to your business.
Rewards
Rewards take many shapes. What rewards you in a certain interaction all depends on the context, your current needs, and your state of mind. Rewards can be a discount, some loyalty points, a gift card, an extra product, or just a visual surprise. These are the classic reward types we are all familiar with. Rewards can also be provided as monetary gifts, like a balance increase on a digital debit card card or in your digital wallet (think crypto for example). But there are also non profit approaches to rewards. As in a person being rewarded with a donation to a cause, made in their name. A powerful way for a business to show how they address issues and back causes, while creating and strengthening loyalty with their target audience.
But beyond rewards themselves and what their monetary values are, we need to look at what is to trigger them. Traditionally speaking, in a marketing and sales sense, rewards have been mostly triggered by financial transactions. We want to change this. Our approach is to trigger rewards based on non-financial actions as well. To reward attention. This is where what we call rewarded promos come in.
Rewarded promos are interactive promotions of your offerings, placed in your digital channels, that reward people's attention for interacting with them. Interactions you can center these promos around are several: From watching a video ad, showing up to a physical store/location, downloading an app, visiting a particular part of a website, answering a survey, signing up for a subscription, buying a product, referring friends, actions you define, and the list goes on. The point here is that these interactions span the whole of your leads and customer lifecycles, and by doing so you can use rewarded promos to motivate people further along in them.
Our pledge is to offer the ultimate reward platform and ecosystem: where you are to set up all of your incentives (rewarded promos), define reward types (both your own, as well as rewards from a vast array of providers), and gain insights on what triggers your audience to obtain these rewards.
And if you are sceptical on the effects of rewards, according to an Aberdeen Research paper, “Organizations that provide non cash reward/recognition had an average year over year annual corporate revenue increase of 3x versus others”.
To summarise:
Rewards = 3x Impact
Attention
As businesses have many approaches to creating and maintaining digital attention. If we boil them down we are left with (in an extremely simplified sense), websites and ads. What do I mean by this? Both of these overarching approaches are built with the same interface elements: text copy, images and video, weaved together by effective use of layouts. As with all things in life; if used effectively they can garner great results. But we can’t ignore how this approach, with these elements, is still based on over a 100 year old advertising tropes. One way mass media communication. Not the two way, dialogue based communication that we all have gotten more and more accustomed to, over the last 20 years. Heck, four of the five most downloaded and used mobile apps in the world are messaging/chat based: WhatsApp, Facebook Messenger, Instagram and Snapchat (in that order). So why shouldn’t you supplement your websites and ads with the power of and methodology behind messaging, to create and maintain attention online?
“But aren’t we talking about chatbots now?” you’re saying? No. Chatbots use natural language processing (NLP) to pick up on what you are inputting in them, to search their FAQ articles, and serve you answers to support questions. They are built to offload customer service. We believe a sales/engagement interaction online needs to be proactive and conversation based. And by proactive we mean that the business challenges the lead or customer to make better purchase decisions, based on their input. You can compare this to how you get a call with a sales agent, and when you make a technical support call to customer service. The approach is completely different. And when it comes to how these conversations are to progress (compared to chat bots), we believe in basing them on scripts written by and with your best employees. Again, referring to a great interaction you’ve had with a sales agent. This way you can base all digital interactions on the best in-person ones, without the need of having an actual person sitting on the other end of every online conversation. You get the benefits of your digital channels being more human-like, narrative driven, and attention grabbing, all in a highly scalable format.
Our pledge is to offer you a attention creating, proactive conversation platform, where you are to easily create conversation flows, using engaging multimedia and rewarded promos, to communicate with - and not just to - your audience.
And if you are wondering if two-sided conversations online work, according to Shoppop [2]: “Conversational experiences in chat are way more effective at converting than traditional landing pages. To be precise, they have proven to convert 3-4x better”.
To summarise:
Conversational Attention = 3x Impact
Artificial Intelligence (AI)
Where does AI fit into sales and customer engagement? Your instinctive reaction might be that it answers your questions, just like the standard customer service chatbots (again, talking about NLP). I have to break it to you - your instinct is wrong. As we have described before (here “A Commerce AI that performs like your best sales reps”), a strong sales AI is hyper personal, takes control and challenges a customer through a two way conversation. What we need then is not first and foremost an AI that interprets text input to an answer. Rather, we need an AI that recommends content and the next optimal/most relevant/suggested action for the user to progress.
What modern marketing and sales needs, is the same type of AI-driven recommendation systems as your favorite music or video streaming services use, to recommend you the best content at any given moment. A marketing and sales recommendation engine needs to:
Be a platform where all possible data signals are captured, so that every lead and customer interaction is something the AI engine learns from.
Produce and present the next optimal action and/or content, based on data signals though a smart adaptive AI agent model.
Produce recommendations like the ones mentioned above, in real time (subsecond).
Our pledge is to offer businesses the ultimate real time, AI-driven, marketing and sales recommendation platform. This in-house developed SMOC.AI technology; our Choice Graph Data platform and our Wizer Recommendation engine, is what fuels all aspects of our software platform.
And machine learning based recommendations work. Wharton Business School [3], who researched one of the simplest models related to this; Collaborative Filtering, says : “Purchase-based collaborative filtering (“Consumers who bought this item also bought”) causes a 35% lift in the number of items purchased over the control group (no recommender) for those who purchase”.
To summarise:
Recommendation AI = 1.4x Impact
10+x Impact
Lets combine the SMOC platform’s 3 core pillars into one, reinforcing the formula:
Rewards x Attention x AI
= (3 x 3 x 1.4) Impact
= 10+x Impact
I hope that this has given you an understanding of where SMOC.AI is coming from, and a glimpse at the possibilities that lay ahead. If you have any questions don’t hesitate to reach out, and the same goes for if you want to apply our formula to your business, today.
