Make Offline Marketing Amazing Again: The Future of B2C Advertising with AI

Across its wide-ranging applications from agriculture to large-scale manufacturing, AI is ubiquitous. In an age of deep technology and cutting-edge research, AI may even be the default in systems which depend on large amounts of data to make valuable predictions.

Ironically, the success of AI systems is still heavily restricted by its ability to collect data from the real world across different sources. In marketing, one of the biggest sources – you guessed right – is offline data.

Put simply, offline data can be understood as data used for data-driven marketing that has been collected from an offline source. This also includes any kind of offline data collected from third-party research companies through street surveys, house visits, or phone calls.

Data such as contact information, footfall traffic, purchase histories, loyalty card data, demographic data and more, are examples of offline data.

So… What’s the problem?

For small businesses that focus mainly on offline sales in their shops, there is no practical way of collecting offline data to aid marketing efforts. Furthermore, even if businesses have the budget to employ third-party research companies to do the job, offline data collection is often time-consuming and labour-intensive.

Instead of spending huge amounts of money for market research, many small business owners opt to rely on memory and rough guesses to design their marketing campaigns.

AI-mazing marketing for everyone

Thankfully, a data-driven marketing and analytics startup, Aimazing, is determined to help businesses solve this tricky problem. To understand how AI plays a part in offline marketing, I spoke to Jun Ting, serial entrepreneur and founder of Aimazing, who has been working to perfect the solution for the last five years.

Read the interview extract below to learn how Aimazing plans to make offline market amazing again!

What problem does Aimazing solve?

We help SMEs and businesses engage and capture their customers through a simple plug and play POS (Point of Sale) product. F&B or small retail businesses can use our solution to identify and directly engage their customers to encourage repeat visits. This has been a blind spot in retail customer engagement for the longest time.

Our product is the digitising of offline transaction data without any integration to Point of Sale (POS) devices. This also greatly increases the efficiency of data collection for market research companies. Usually, when companies run online campaigns, it is often difficult to measure the impact of these campaigns from offline transactions.

Aimazing acts as a tool to fill this knowledge gap by providing a real-time analytics dashboard for our merchants to track their offline data effortlessly.

The COVID-19 situation hit F&B and retail owners extremely hard. How did Aimazing’s solution help them tide through this unexpected difficulty?

Before the pandemic happened, most of our clients were only interested in how to harness data analytics to make more money. However, when COVID-19 hit our shores, our clients were forced to reorder their priorities. Because of a series of lockdown measures implemented over several months, they struggled to retain footfall at their physical shops.

We wanted to know how best to solve their problems, so we conducted market surveys with our clients. It became apparent quite quickly that many of them are already integrated with the biggest retail platforms in Singapore such as Fave, Grab, and Shopback.

However, the campaigns that our clients were running with these giant digital platforms weren’t able to give them a sufficient understanding of their own customer base. This is because, while these platforms allow merchants to evaluate the number of customers that visit the store each day, important customer information remains in the hands of the digital platforms and are not accessible to the individual merchants.

Hence, when individual merchants approach third party marketing agencies to help run their own marketing campaigns, the “customer data” that these shops can provide are, at best, based on their own memory, rather than on concrete data collected. This had to change because it was not solving the problems that our clients were facing.

We began work on an MVP as soon as we could in May and officially launched one month later in June 2020.

It was built to solve a problem and has key features that work well for our clients. One of them is our automated messaging platform which is integrated with Facebook. For example, if a merchant’s customer has not returned to the store for more than 30 days, the system will send a simple reminder.

This way, our clients can run their very own cash back programmes whilst enjoying seamless online communication with their customers. Further, with the data gathered online, Aimazing’s proprietary AI algorithm can identify specific target segments for subsequent marketing campaigns – this solves another problem for those with marketing agencies or running social media campaigns.

Our data helps them target their real customers and provides a proper demographic of users rather than an estimation.

Hmm … Can this be done without AI? How does Aimazing employ AI in smart ways to help?

The biggest benefit that comes with using AI is that it greatly reduces operational costs. Our proprietary AI is like a silent expert who handles all the backend tasks for our clients. Our AI can analyse mountains of collected data and provide actionable insights to the Aimazing team, who can in turn provide clear guidance to clients.

Our AI does this through analysing the spending patterns of each customer. At every step of the way, Aimazing works around our client’s priorities to achieve the best results for our clients. For small F&B and retail outlets, we sometimes build customised basket analytics for them.

We see the use of AI as a way to effectively scale the ability to provide the right marketing data and tools to small outlets that usually do not have a huge marketing team.

Do you think Aimazing’s solution could be seen as a manipulative marketing tactic?

That is an interesting thought. I’ve never actually thought about it this way, but at Aimazing, we want to create an effective marketing tool without compromising consumer privacy.

First and foremost, our main goal is to remind our customers of their unused credits which may have slipped their minds. But if our customers choose to not be reminded of them, they can easily unsubscribe without any incurring penalties.

Secondly, AImazing and our merchants are unable to retrieve customers’ personal data through Facebook messenger. The only data we have of our customers are their PSIDs (Page Scoped-ID), an identification number unique to every Facebook Page customer visits. Thus, the only thing we know is our customer’s spending patterns.

We do not know their name, address, email address, mobile number, or any other personal data, even if they have been provided on their Facebook profiles. This means we do not store or mine consumer data, making it safer for consumers as compared to other more intrusive products.

Ultimately, AImazing’s solution is focused on helping our merchants to reach out to their loyal customers who may have forgotten about their discount vouchers.

This is where AImazing comes in to help both our merchants and their customers to achieve their objectives. Honestly speaking, you can just think of us as a reminder service with no personal agenda.

In your opinion, what do you think is the future of B2C marketing?

Wow, this is a really difficult question. In the current online marketing landscape, we have already reached an SKU (stock-keeping unit) level of data. This means that when you search for something on Lazada, you will also see relevant products on digital platforms like Facebook, Google, and Instagram.

However, when you shop offline, there is no way to build such a personalised space for each customer, because we’re constrained by bad data and the lack of a platform or system agnostic service –  i.e, an unbiased view of data. This presents an opportunity for AImazing to be the bridge between retailers and customers in the offline space in much the same way as social media and search engines have done for the online space.

I strongly believe retail will have a resurgence soon, they just require a better solution to empower the merchants to be able to effectively market to their customers.

My dream is to make offline advertising both easy for merchants and relevant to each customers’ wants. I am confident that AImazing will re-define B2C marketing in the near future.

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