Introduction

Many business leaders see the value of AI and automation. So why aren’t companies embracing it wholeheartedly?

50% of businesses will use AI at scale over next years, while 65% have already adopted RPA.

Businesses in all industries are being squeezed, with higher demands from both customers and stakeholders. They need to find new ways to work, with fewer errors, faster outcomes, and higher productivity.

Artificial intelligence is the perfect complement for human intelligence. Humans are creative, imaginative, tactical, strategic… while AI is able to analyse vast amounts of data and identify patterns without exhaustion.

At this new age, AI works together with humans to amplify our capacities, which implies far-reaching changes in the structures of businesses.

The market for automation technologies such as RPA (robotic process automation) is growing by 20 per cent per year, and it will reach $5 billion by 2024 . Reflecting this trend, the number of businesses that have successfully scaled the automation implementation has doubled since 2018.‍

Over the next three years, executives expect automation to increase their workforce capacity by 27 per cent: equivalent to 2.4 million extra full-time employees.

Statistics, however, don’t tell the whole story. Businesses are starting to investigate the possibilities of RPA, but this new scenario requires us to be able to imagine and identify scale opportunities.

Despite the adoption rates for automation, businesses are only deploying AI in a limited capacity. Only 3% of organisations have scaled their digital landscape.

Why does this happen? Usually, AI is commissioned by marketing stakeholders– Sales, Channel, Product– to achieve specific objectives. Automation is seen as a point solution, used to solve just one niche problem, instead of considering it as an asset to enhance your team’s capacities (using AI as a new colleague, fully data-driven).

In this book, we’ll cover some of the common stumbling blocks for AI, then delve into solutions to help you scale your marketing efforts.

1. Global Market Insights, “To 2024, robotic process automation market to see 20% CAGR,” MarketWatch, October 5, 2018.

Has your growth already reached its upper limit?

Growth projects usually start off with a small-scale proof of concept. The test is deployed in one discrete vertical or segment, usually to test and validate its results.

When deploying growth projects, a proof of concept is usually an affordable, quick to launch action that can escalate through the backlog, as it doesn’t need a huge decision-making process to implement. For many businesses, it makes complete sense.

Validation and deployment site-wide, therefore, end up in a bottleneck affecting your product’s growth velocity, affecting roadmaps and the global overview overgrowth.

Enhancing your growth team through AI creates obvious efficiency and speed benefits, but if you aren’t taking a ‘big picture’ view on how your product and users can benefit from it, you’ll accelerate your growth rate… rather than using AI to reimagine how your product improves his market fit.

Here are a couple of simple tips to avoid this ‘Growth ceiling’.
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1. Get subject matter experts and stakeholders involved early

Non-IT professionals can implement AI processes, but they are rarely the ones who are given the responsibility. IT and operations are most likely to have a full view of where and how automation could benefit other areas of the business, but their technical expertise needs to be matched up with the people who take care of the product growth day to day. Those teams may also be working on something similar already, so you can avoid duplicated work by joining forces.
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2. Build the expertise on the solution

When there aren’t experts on the solution within the company, you can end up becoming reliant on external service providers, consultants and contractors who will take the knowledge with them when they leave. As you expand your digital workforce, you should also begin to build a team who can take ownership of the developing knowledge and also maximise the output your business can obtain from it.
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Has your product backlog outstripped your growth team ability to deliver?

Most companies will experience ‘product overload’. This is where their product is so successful and well-received by users, that there is a clamour to get more deployed, which will end up displacing actions aimed at sustaining growth.

On the one hand, it’s not a bad problem to have. You’ve done a great job of getting your users on board with your product concept, and they are committed to its progressive feature discovery.

However, you run two risks in this case.

Firstly, the queue for product features or optimisations may grow out of control, and your project will lose momentum as users lose enthusiasm.

Secondly, you might not always be able to replicate the same level of success as your initial product pilot. In which case, your product growth will be diluted, and automation loses its shine.

Preventing it is easily achieved, but it requires commitment.
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1. Choose the right areas where to focus on growth

The most successful companies are using Lean techniques to analyse, map and identify the right levers to pull. You can work with Data analysts, Lean specialists and the growth team to identify the insights you need. Then use that knowledge to choose suitable projects or areas for growth. You will soon experience an improvement on the speed and quality of your growth projects, by just focusing where it matters.
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2. Choose the right AI for the right task

The offer of AI solutions is growing each day. Each implementation has a cost plus a learning curve associated, so aligning with your most important growth levers will be critical to maximising not only the results from it but also the necessary roadmap deviation. Choose always an impact where it truly matters over the implementation required from your dev’s end.

Has your marketing team kept up with the latest trends and opportunities?

Through effective data analysis and the ability to adapt to every possible input, AI in digital marketing enables to save time and resources while maximising the results on digital marketing activities.

Here’s how AI in digital marketing can provide a competitive edge:
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1. Helps you understand your audience better: AI can analyse large data sets to predict buying behaviours easily and your user’s drivers to make better product-related decisions.

2. Improves user experience: AI can provide a granular content to your audience, adapting to the solution/content that they need.

3. Increases the efficiency of your marketing efforts: Through data-driven analysis, AI can provide information on which is the more effective marketing strategy for your business.

4. Increases the productivity of your team: AI algorithms provide an opportunity to automate the outputs on data-driven decisions, increasing both scale and productivity of the marketing teams.

5. Increases ROI: AI empowers not only decision-making but also helps to create a better performing output from your strategies while reaching the right audience for your product.

38% of consumers think that AI will soon improve customer service. And 73% of them are open to businesses that use AI.
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Which challenges have companies faced while implementing AI?

Lastly, we have to acknowledge that AI or growth automation is a loaded term – for many people, there are concerns about job security whenever automation is mentioned. The more you plan to expand your automation project into new areas of the business, the more critical your communications are to its success.
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Opportunities in AI

AI should be used for focusing on opportunities, rather than cost reduction; which is the powerful message that you want to communicate across. – especially to risk-averse business leaders who are concerned about job losses. Needless to say that any robotic intelligence needs to incorporate the experience of each professional to achieve his objective; AI needs to be seen as a tool that allows automation and scale, adding ease to your team's objectives, while allowing the possibility to achieve even higher results, by enhancing your teams capacity. For example, it can create new revenue streams for business units, making the existing staff more productive, or it could allow a marketer to take actions site-wide while only changing a configuration file.

If interest is low, fostering competition between potential ownersis sometimes an excellent way to generate buzz, instead of chasing them individually for budgets or instructing other team members.
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Acceptance‍‍

Part of the challenge is helping existing staff understand how they’re going to interact with the AI, and showing them that automation is accessible to them. It’s essential to establish this early on and to pick the right AI partner to support and advise you.
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Naming the bots can help staff to embrace them as virtual colleagues. For instance, it helps to know ‘Bob’ is a finance employee running a monthly analysis on the SEO status. On a practical level, it helps with internal processes too.

How does success look like?

None of these challenges should distract from the end goal – a digital resource that fundamentally improves the results how your business operates. For companies that set up correctly and scale their automation projects sustainably, the results are often outstanding.
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Tomorrow Sleep boosted Web traffic by 10,000%

Sleep system start-up Tomorrow Sleep launched in 2017 and started creating content. After several months of pushing out top-quality content, they were averaging around 4,000 users to their site every month. Until they began using an AI-powered content intelligence and strategy platform.
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It used the platform’s application to understand which high-value topics the company needed to be talking about and to see where competitors ranked for each of these topics.

SEE THE CASE STUDY
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How eBay Writes Thousands of Email Subject Lines in Minutes

With billions of products to choose from and millions of customers to serve, eBay was looking for a way to make each customer feel like they were the only person in the world that mattered.

eBay turned to artificial intelligence and tested AI-powered copywriting tool, using natural language generation and deep learning to be capable of learning a brand’s voice and automatically writing optimised email subject lines, Facebook ads, and push messages. These personalised subject lines were then A/B tested at scale with eBay’s millions of customers, all in the matter of a few minutes.

SEE THE CASE STUDY
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Support to get started

We’ve covered a lot in this book. Perhaps an idea jumped out and inspired you. Or maybe you recognised your business in several of the pain points and solutions, and you’re not sure where to start. Either way, partnering with DWX can help.

We spend all our time-solving challenges for our customers, and we’ve learned from real-world successes. We can help you focus and refine your vision with a free 121 session on how to drive more traffic, automate growth processes, scale efficiently and capitalise new opportunities quickly for your business. And when you’re ready to move, we’ll help you get off and running fast, while leading the future of the Internet.