In today’s digital world, everyone leaves a footprint. These footprints lead to data which marketers can use to follow the trail a customer leaves. Crucially, the marketer can use this information to plant signposts along the way, influencing the customer’s journey.
In the past, getting this information took time and effort. But now, algorithms, tracking codes and advancements in technology such as machine learning and artificial intelligence (AI) mean that this process can be almost entirely automated, sparking insights throughout the sales lifecycle that humans otherwise would not see.
What is account-based marketing?
These insights and processes are allowing marketers to become more laser-targeted than ever before, which, for the B2B sector, is opening the door to a more effective method of account-based marketing.
In the past, B2B marketing would often involve an almost scatter-gun approach, firing out broad messages to relatively random prospects and hoping to stumble upon someone interested in your product or service. In fact, you’ve probably received plenty of completely irrelevant marketing emails or cold calls that are bordering on spam.
But account-based marketing (ABM) allows for a much more focused approach. ABM is a strategy that arms the marketer with the data and insights they need to target prospects that have been identified as a good fit, concentrating efforts on those would-be customers that are more likely to be interested, using personalized messages that speak to their specific needs.
As the Information Technology Services Marketing Association (ITSMA) defines it, ABM involves treating individual accounts “as markets in their own right.” When used well, it is a more efficient use of a marketer’s time, honing in on relevant targets with an approach that stands a higher chance of leading to a conversion.
Personalization is key to successful ABM
The granular level of detailed insight available through the use of AI allows marketers to turn an otherwise generic message into a highly personalized pitch. This personalization is more likely to get you a foot in the door, driving higher response rates and steering the prospect towards the next step of the sales funnel.
ABM is all about making sure your marketing budget goes towards those most likely to buy. But, first of all, you have to identify those targets with the most potential. Up until now, that meant marketers had to base their campaigns on assumptions or waste a lot of time on cold calling.
That may have seemed acceptable for larger companies with high-value customers, but not so good for smaller companies looking for new business. Even with the big companies, always chasing the low-lying fruit can make marketers oblivious to new areas of growth.
How AI can help you make it more personal
It is data that underpins the success of personalization. The more data, the better – but then the bigger dataset you have, the more sorting there is to be done. AI can collate, categorize and identify connections within massive pools of data, without human error or assumptions. That’s not to say AI should replace people. The human element is still very much needed. After all, you’re targeting people, and the way to do that is through emotion.
Algorithms haven’t yet nailed ‘emotion’. However, they can provide the automation to process massive quantities of data and turn it into insights you can then use to make your campaigns more effective.
Everything is already in place for AI to come along and do its job. All the data is there, we’ve been mining it for years, and we produce more and more of it every day (2.5 quintillion bytes daily at the last calculation). That’s far too much for us even to attempt to process without the help of machines to do the grunt work. But the more data you have, the faster the algorithms will learn, with each interaction leading to higher levels of accuracy.
Putting AI to work through ABM
Data is no good for your ABM campaigns if you don’t have the means to analyze it and the tools to put it to work on personalizing your campaigns. It is an approach that aims to cut down on the heavy lifting of manually researching leads and reducing the wastage of hours spent trying to sell to prospects that are never likely to convert. For example, the use of predictive analytics in ABM uses data modeling to predict whether or not a company is a good fit for your service.
ABM works well for higher value services, as it suits longer sales funnels where there is a clear return in spending time building personal relationships with those earmarked prospects. It also delivers a stronger ROI by making that time spent more likely to lead to a sale.
While it suits big ticket businesses, a growing number of SaaS services and companies are also making AI more accessible to companies of all sizes, lowering the barrier of entry to AI-powered ABM and making it more cost-effective than ever.
1. Identifying prospects:
Clearbit, for example, uses its Reveal technology to transform seemingly anonymous web data such as IP addresses into complete company profiles. This information can tell you a lot about visitors and help you personalize your campaigns.
Whereas researchers were spending minutes at a time Googling contact details or scouring LinkedIn profiles to find out the best person to contact and work out whether a company was a realistic sales target, Clearbit scans the data to identify the worthwhile prospects in an instant. Its integration with Salesforce, the go-to CRM software for many sales teams, puts this information right where you need it, pasting the data and demographic details directly into the record for your sales teams to access.
2. Nurturing leads:
As well as identifying prospects, AI is also playing a key part in retaining and nurturing those prospects. An effective ABM strategy doesn’t focus purely on new business, but also developing and growing those existing customers, increasing your customer lifetime value through cross-selling or upselling new and relevant opportunities.
But as your account base grows, it becomes more difficult to maintain a personal relationship with each customer. Data and AI can help, allowing you to automate the creation of highly personalized email campaigns that have been proven time and time again to optimise retention rates.
3. Retaining customers:
Traditionally, retention campaigns tend to be generic. Customers can see through that straightaway, binning emails on sight. AI can present data in a way that’s more personalized for customers, offering insights for improvement that’s directly tied to customer data points. This allows you to address their pain points, show an understanding of their needs, and modify your messages to suit their behavioral patterns and the point they are in the sales funnel.
4. Automated messaging and dynamic content:
B2B marketing platforms such as Demandbase are using machine learning to solve challenges at every step of the funnel, including predictive analysis of prospects, using natural language processing (NLP) to understand user intent, and identifying the most relevant content to serve to the right prospects at the right time. Various communications platforms, such as Conversica and Dotmailer are using machine learning to power automated messaging or dynamic content, reducing the manual work needed for effective personalization. Artificially intelligent platforms are also sounding more and more human, thanks to advances in NLP and from services such as Narrative Science.
5. On-site personalization
Even your own website content can be personalized and play a part in ABM, with platforms such as Sentient Aware using evolutionary algorithms to instantly learn and identify what content would be most relevant to each visitor based on their previous visits or real-time interactions. Imagine fine-tuning your web content to match what a prospect is interested in, or showcasing a new service upsell to an existing client whenever they visit your site? Powerful stuff for the lifetime value of your customers.
You can even use AI to help optimize your content presented on external sites. Advertisements on other web properties are becoming more intelligent, allowing you to supercharge your retargeting campaigns, communicate with prospects directly through ad content or gain more learnings about those that have interacted with it.
Powering multi-channel AMB
With AI now powering individualized content across email, instant message, social media, advertisements, website content, text and more, marketers have the opportunity to create a truly multi-channel personalized experience. This has the potential to be incredibly powerful for account-based marketing, driving engagement, relevance and targeted messaging for your highest value prospects and customers.
Worldwide ad spending is at an all-time high, yet many marketers are still blasting messages blindly and complaining about poor outcomes. AI has the potential to change all that and deliver far more bang for your buck, and we’ve only just scratched the surface.