The Personalization Technology Build vs. Buy Conundrum, Part 1

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The Personalization Technology Build vs. Buy Conundrum, Part 1

November 28, 2017 by

As we at Evergage continue to meet and engage with some of the world’s largest retailers, financial services firms and technology providers, we inevitably run into situations where businesses are considering two different approaches to personalization: build in-house or buy a vendor solution.

We understand the debate. Larger companies have teams of talented engineers who play a vital role in helping their company perform and innovate on a regular basis. These engineers know the company’s business, its products and solutions, and its customers. So when it comes to developing a personalization solution, what’s one more project?

At Evergage, we refer to this as the personalization technology build vs. buy conundrum. We can appreciate the quandary that many companies face, and, as an outside vendor, we’re in no position to know exactly what’s right for your business. Instead, we can provide information that is helpful in the decision-making process, and we can offer our perspectives on the challenges and trends related to personalization technology and functionality. In this two-part blog series, I outline a number questions that you and your team may want to consider when faced with a build vs. buy conundrum.

What Business Are You In?

I’m a fan of the show Shark Tank, where entrepreneurs pitch business ideas to a panel of potential investors (a.k.a. sharks). Not ones to mince words, the sharks are often quick to point out when an entrepreneur doesn’t understand his or her true business. For example, it’s not uncommon for an entrepreneur on the show to have gained some traction selling a particular product. And rather than focus on the manufacturing side of things, the sharks may encourage him – especially given limited resources – to focus on what he does best (i.e., sales and marketing) and leave the manufacturing to someone else.

Similarly, when considering building any technology solution in-house, it’s always best to ask what business you are really in. Depending on your industry, your primary focus is likely on making, delivering and supporting the best possible products and services that meet – and hopefully exceed – your customers’ expectations. Building personalization technology, particularly with all the complexities involved, is likely not a core part of your business.

If your needs are so unique that no solution exists to solve them, then it may make sense to develop in house. But if not, why build? Would you build an in-house CRM application, an email platform, an accounting system or a web analytics solution today? Of course not. Why? Because these are not your core business competencies and cost-effective, highly functional best-in-class solutions are readily available. The same holds true for personalization solutions.

The Evergage platform is a powerful solution that is delivered at a fraction of the upfront and total long-term cost of what it would take to develop an in-house-built solution. And with Evergage, you don’t need to pull engineering or IT resources from projects that are critical to the operation of your core business.

Can You Build a Complete Platform?

Let’s use another TV show analogy. Have you ever watched one of those shows like Renovation Realities, where regular people are filmed renovating their own houses without any help? Inevitably, the renovators discover that what they thought would be easy is actually a lot more complicated than they anticipated. Personalization is a lot like that. You may initially think that you just need the ability to track a few data points, plug them into a basic rules engine or a simple algorithm, and deliver a relevant experience.

But delivering one-to-one experiences requires much more than that. You need to be able to collect data and deliver experiences across channels including desktop web, mobile web, web applications, mobile apps, on-site search and email. You need to capture deep behavioral data that goes well beyond “clicks,” combine it with data from other sources, and use it to create a unique profile for each person (known or anonymous). You need to understand what a person’s behavior says about her interests and in-the-moment intent within the context of your actual business. You need to deliver sophisticated analytics and attribution measurement, and much more.

Accomplishing all of this is certainly possible, but it takes a significant investment in time and resources. We’ve been building, refining and evolving our platform since 2010. And while there will always be more work to be done, what we’ve built so far is unrivaled. We offer an incredibly powerful solution for a fraction of the cost it would take to develop a not-even comparable in-house solution.

Can You Develop Machine-Learning Capabilities?

At the end of the day, personalization is about improving the customer experience. As a consumer yourself, what are some of the best customer experiences you’ve had? If you’re like most people, you’ve found that some of your best experiences are from companies that recognize you as an individual and make it easy for you to accomplish your specific goals. In other words, those companies that can treat you as an individual, rather than a random person.

Marketers have dreamt about the ability to communicate with prospects and customers at the one-to-one level for over 25 years. Now that the ability to do this is actually possible with machine learning, why would you ever invest your efforts in a personalization technology that didn’t allow for one-to-one communication?

Machines can combine many different sources of data, draw insights about what that data says about an individual, and select the most relevant experience to deliver. While a good personalization platform will make it easy for a marketer to leverage and even customize machine-learning algorithms, the development of the underlying algorithms requires sophisticated data science engineers.

Evergage has been developing our machine-learning capabilities for many years (in fact, we recently wrote the book on using machine learning for one-to-one personalization). Our algorithms were designed to ingest, understand and process deep behavioral analytics data — and to make it easy for a marketer to use. It is unlikely that this can be developed in your organization without taking significant time from data science engineers.

Can You Seamlessly Integrate Into Your Tech Stack?

An IT director at a large, well-known apparel retailer recently confessed something to me – he admitted that they have a data problem. It’s not that they don’t have enough data; it’s that they have too much data and it resides in systems that don’t integrate with one another.

This is a common theme when talking with prospective customers. In fact, if I had a nickel for every time I’ve heard a similar challenge, I’d have enough to buy myself a lovely lunch by now.

Depending on the company and industry, customer and prospect data can exist in any number of technology solutions – CRM, ESP, MAP, DMP, analytics tools, e-commerce platforms, SaaS applications, mobile apps, and more. Effectively utilizing and combining all this information often makes the difference between delivering a great customer experience and a poor one. But integrations – as any IT director will tell you – are cumbersome, time-consuming, challenging, and rarely allow for data to be acted upon in real time.

But at Evergage, we are well versed in working within existing technology stacks. Evergage wasn’t built just to be a personalization platform, it is also a customer data platform (CDP) that allows you to bring data in from and push data out to other systems. With Evergage, you’ll begin collecting deeper behavioral data on customers than ever before – information that’s used to develop affinity models. And then you’ll be able to layer in information from existing data sources, such as online or offline transactions, account records from a CRM application, or segments from your email service provider. These details can be combined within a unified customer profile (UCP) where they can be used to deliver rule-based and/or machine learning-driven experiences – all in real time.

Final Thoughts

In this blog post, I’ve outlined a few of the questions you should consider when deciding whether to build your own personalization solution or invest in Evergage’s real-time personalization platform. You need to ask whether it is worth taking the resources away from your core business, whether your internal teams can deliver a complete personalization platform, how well your team could deliver machine-learning capabilities, and whether you can integrate all the separate sources of data you have into a customer data platform.

Download our new whitepaper, Build vs. Buy: Selecting the Best Option for Your Personalization Solution, for more detail on each of these questions and more. And stay tuned for part 2 of this blog post series.

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